% =========================================================================== % % Header for Hypathia Electronic Library % % =========================================================================== % % BibTex-file{ % author = {Moddemeijer, R.}, % address = {University of Groningen, % Department of Computing Science, % P.O. Box 800, % NL-9700 AV Groningen, % The Netherlands}, % filename = {ModdemeijerR.bib}, % url = {ftp://ftp.cs.rug.nl/pub/users/rudy/ModdemeijerR.bib}, % telephone = {+31 50 363 3940}, % fax = {+31 50 363 3800}, % email = {rudy at cs.rug.nl}, % www-home = {http://www.cs.rug.nl/~rudy}, % dates = {1959--}, % checked = {R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999}, % entered = {R. Moddemeijer, rudy at cs.rug.nl, 17 March 1999}} % % =========================================================================== % % Header for BibNet - A Bibliography Network Project % % =========================================================================== % % Contributor's Last_name: Moddemeijer % Contributor's First_name: Rudy % Contributor's E_mail_address: rudy at cs.rug.nl % Bibliography format: % Author/Contributor's Affiliation: University of Groningen, % Author/Contributor's Department: Department of Computing Science, % Author/Contributor's Address: P.O. Box 800, % Author/Contributor's City_state_zip: NL-9700 AV Groningen, % Author/Contributor's Country: The Netherlands % Author/Contributor's Phone: +31 50 363 3940 % Author/Contributor's Fax: +31 50 363 3800 % Author/Contributor's URL: http://www.cs.rug.nl/~rudy % % =========================================================================== @InProceedings{Moddemeijer:2000:AOE, author = "R. Moddemeijer", title = "Autoregressive order estimation combined with pruning of the coefficients", booktitle = "Signal Processing Symposium (SPS 2000)", address = "Hilvarenbeek (NL)", publisher = "{IEEE} Benelux Signal Processing Chapter", month = Mar # " 23-24", year = "2000", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM0001.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/posters/RM0001.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM0001.ps.gz", checked = "R. Moddemeijer, rudy at cs.rug.nl, 27 March 2000", entered = "R. Moddemeijer, rudy at cs.rug.nl, 10 November 1999", note = "Published on CD-Rom", abstract = "A correctly derived Auto Regressive (AR) model can not always optimize the intended approximation. An optimal model should balance bias, caused by under-fitting, and additional variance, caused by over-fitting. The selection of this optimal AR-model is a combination of AR-order estimation and the reduction of the number of coefficients by pruning. We leave the classical approach of AR-order estimation and replace it by AR-coefficient selection. As a selection criterion we use the Modified Information Criterion (MIC), which is closely related to Akaike's criterion (AIC) and has a guaranteed a priori chosen over-fitting probability. We present our algorithm and its verification by simulations.", } @InProceedings{Moddemeijer:2000:DEE, author = "R. Moddemeijer", title = "The Distribution of Entropy Estimators based on Maximum Mean Log-likelihood", editor = "J. Biemond", booktitle = "21st Symp. on Information Theory in the Benelux", address = "Wassenaar (NL)", month = may # "25-26", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", publisher-url = "http://ei1.ei.ele.tue.nl/wic", year = "2000", pages = "231--238", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM0002.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/posters/RM0002.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM0002.ps.gz", ISBN = "90-71048-15-2", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 March 2000", entered = "R. Moddemeijer, rudy at cs.rug.nl, 29 May 2000", abstract = "Entropy estimation is often based on the Maximum Likelihood (ML) method. When the probability density function sufficiently models the reality, the maximum average log-likelihood is a good (negative-)entropy estimator. Previous work from the author suggests that, under certain conditions, the variance of such a statistic consists of a basic variance, plus a number of statistically independent contributions corresponding with the independently adjustable parameters of the pdf. Conform this assumption we derive and justify under certain conditions the distribution of a ML-based entropy estimator. This knowledge about the distribution can be used to bridge the gap between process and application of optimal models, in particular for the selection of an optimal probability density function in the presence of superfluous parameters.", } @InProceedings{Moddemeijer:2000:DTM, author = "R. Moddemeijer and L. Spaanenburg", title = "A decomposition technique for modular neural networks", editor = "J. P. Veen", booktitle = "Proceedings of the 11th workshop on Circuits, Systems and Signal Processing ({IEEE}/{ProRISC2000})", address = "Veldhoven (NL)", month = nov # " 30-" # dec # " 1", publisher = "{STW} Technology Foundation, Utrecht (NL)", year = "2000", pages = "???--???", ISBN = "90-73461-24-3", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM0003.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/posters/RM0003.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM0003.ps.gz", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 October 2000", entered = "R. Moddemeijer, rudy at cs.rug.nl, 6 October 2000", keywords = "order estimation, mutual information, data interference, classification, modular neural networks", note = "Published on CD-Rom", abstract = "Modularity is required to resolve the data interference problems that usually plague monolithic designs. The presence of data interference shows from the learning curve of the net. Re-learning does not always remove the problem; then a modular structure can be used. However, there is no guarantee that data interference can be removed in the simple decomposition. Ensemble networks and mixed experts can be used for specific decompositions. On the other hand, there is not a generalized constructive method to achieve an efficient modularity. In this paper an information-theoretical approach to the decomposition of modular neural classifiers is presented, that allows for arbitrary hierarchies.", } @InBook{Moddemeijer:2000:DTMa, author = "R. Moddemeijer and L. Spaanenburg", title = "A decomposition technique for modular neural networks", editor = "H. Varwijk and J. P. Veen", booktitle = "Abstracts of the workshps {SAFE99}, {ProRISC99} & {SeSens}", address = "Veldhoven (NL)", month = nov # " 29-" # dec # " 1", publisher = "{STW} Technology Foundation, Utrecht (NL)", year = "2000", pages = "108", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 December 2000", entered = "R. Moddemeijer, rudy at cs.rug.nl, 6 December 2000", ISBN = "90-73461-23-5", } @InProceedings{Dantzig:1982:DMP, author = "R. Moddemeijer {R. van Dantzig, G.J.F. Blommestijn} and I. Slaus", title = "On the deep minimum in proton-induced deuteron breakup", booktitle = "Proceedings of the International Conference on Nuclear Structure", location = "Amsterdam (NL)", publisher = "Nederlandse Natuurkundige Vereniging, sectie Kernfysica", confdate = "Aug. 30 - Sept. 3, 1982", year = "1982", pages = "17", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8201.html", checked = "R. Moddemeijer, rudy at cs.rug.nl, 8 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 7 April 1999", } @Masterthesis{Moddemeijer:1983:BAR, author = "R. Moddemeijer", title = "Berekening aan de reactie {D}({P},{PP}){N} bij 50 Me{V} en vergelijking met een bol experiment", school = "Nationaal Instituut voor Kernfysica en Hoge-Energiefysica (NIKHEF)", address = "Amsterdam (NL)", number = "PIMU 83/1", year = "1983", checked = "R. Moddemeijer, rudy at cs.rug.nl, 7 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 7 April 1999", language = "Dutch", } @Masterthesis{Moddemeijer:1983:DA, author = "R. Moddemeijer", title = "De damborddetector anno 1983", school = "Nationaal Instituut voor Kernfysica en Hoge-Energiefysica (NIKHEF)", address = "Amsterdam (NL)", number = "PIMU 83/2", year = "1983", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 7 April 1999", language = "Dutch", } @InProceedings{Moddemeijer:1983:FPS, author = "R. Moddemeijer and G. J. F. Blommestrijn and R. van Dantzig and C. Stolk and J. A. Tjon", title = "Full phase space calculation with the Reid potential for the reaction d(p,pp,)n at {E} = 50 Me{V}", location = "Petten (NL)", publisher = "Nederlandse Natuurkundige Vereniging, sectie Kernfysica", confdate = "Nov. 11, 1983", year = "1983", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8303.html", checked = "R. Moddemeijer, rudy at cs.rug.nl, 3 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 7 April 1999", } @TechReport{Moddemeijer:1984:ABV, author = "R. Moddemeijer", title = "{AAMI} bijdrage van buiten het $3\sigma$ gebied bij een binormale verdeling", institution = "Technische Hogeschool Twente", address = "Enschede (NL)", number = "077.2519", year = "1984", keywords = "mutual information, bias", language = "dutch", checked = "R. Moddemeijer, rudy at cs.rug.nl, 22 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @InProceedings{Moddemeijer:1985:EEM, author = "R. Moddemeijer", title = "Estimation of entropy and mutual information of continuous distributions", editor = "A. J. Vinck", booktitle = "Sixth Symposium on Information Theory in the Benelux", address = "Mierlo (NL)", month = may # " 23-24", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1985", pages = "27--34", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8501.html", ISBN = "90-71048-02-0", checked = "R. Moddemeijer, rudy at cs.rug.nl, 8 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "For time-delay estimation with a maximum average amount of mutual information (AAMI) method, applied to EEG's of epileptic animals or patients, it is necessary to have a simple and reliable method for the estimation of mutual information. We present a histogram based method for estimating a two-dimensional continuous probability density, from which we determine estimatesof the entropy and the mutual information. For this method we derived expressions for bias-correction and variance estimation. We present some simulation results using a binormal distribution and hope to present the first results of the method applied to real EEG's.", } @InProceedings{Moddemeijer:1986:AMI, author = "R. Moddemeijer", title = "An {ARMA} model identification algorithm", editor = "D. E. Boekee", booktitle = "Seventh Symposium on Information Theory in the Benelux", address = "Noordwijkerhout (NL)", month = may # " 22-23", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1986", pages = "151--159", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8601.html", ISBN = "90-6275-272-1", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "To identify from electroencephalogram (EEG) signals the mechanism, which causes the spreading of epileptic seizures in the brain, we use a model identification algorithm. We have choosen for autoregressive and moving average (ARMA) modeling. We present an off-line maximum likelihood (ML) of least squares algorithm, based on an iterative Gauss-Newton minimization. A sytematic parameter search is integrated in the inversion of the Hessian-matrix. The optimal model is selcted with the Akaike criterion. We are able to identify a model in a large parameter space unsing only a few active parameters. Finally we present some promising results.", } @InProceedings{Moddemeijer:1986:EEM, author = "R. Moddemeijer", title = "On estimation of entropy and mutual information of continuous distributions", editor = "I. T. Young et. al.", booktitle = "EUSIPCO-86", location = "Den Haag (NL)", publisher = "North-Holland", address = "Amsterdam (NL)", month = sep # " 2-5", year = "1986", pages = "1033--1035", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8602.html", checked = "R. Moddemeijer, rudy at cs.rug.nl, 8 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Mutual information is used in a procedure for estimation of time-delays between electroencephalogram (EEG) signals. Our presentation deals with a histogram method to estimate entropy and mutual information from signals sampled and discusses its accuracy. The results are compared with earlier work.", } @InProceedings{Dantzig:1985:FPS, author = "R. van Dantzig and R. et. al. Moddemeijer", title = "Full Phase Space Analysis for the pd $\rightarrow$ ppn at ${T}^{lab}_{p}= 50$ Mev", booktitle = "Tenth European Symposium on the Dynamics of Few-Body Sytems", location = "Balatonf{\"u}red, Hungry", year = "1985", checked = "R. Moddemeijer, rudy at cs.rug.nl, 14 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @InProceedings{Moddemeijer:1987:MLE, author = "R. Moddemeijer", title = "From maximum likelyhood to an entropy estimate", editor = "D. Kleima", booktitle = "Eighth Symposium on Information Theory in the Benelux", address = "Deventer (NL)", month = may # " 21-22", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1987", pages = "86--92", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8701.html", ISBN = "90-71048-03-9", checked = "R. Moddemeijer, rudy at cs.rug.nl, 8 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "We present some preliminary thoughts about a method to estimate entropies using the maximum likelihood method. The necessary redefinition and generalization of the maximum likelihood method to obtain this estimate are presented. The estimated maximum of the mean log-likelihood function is interpreted as a neg(ative)-entropy estimate. Two seperate sources of bias can be distinguished: R-bias; caused by insufficient representation of the {"}true{"} probability density function by its estimate and N-bias; due to the finite sample size. Also the variance of our (entropy or mean log-likelihood) estimate is presented.", } @TechReport{Moddemeijer:1987:ITD, author = "R. Moddemeijer", title = "An information theoretical delay estimator", institution = "University of Twente", address = "Enschede (NL)", number = "080.87.45", year = "1987", keywords = "delay, mutual information, entropy, estimation, ambiguities", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @TechReport{Moddemeijer:1987:DCD, author = "R. Moddemeijer", title = "Definition of the concept of delay", institution = "University of Twente", address = "Enschede (NL)", number = "080.87.43", year = "1987", keywords = "delay, estimation, cross-correlation, mutual information, definition", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @InProceedings{Moddemeijer:1988:ITD, author = "R. Moddemeijer", title = "An information theoretical delay estimator", editor = "K. A. Schouhamer Immink", booktitle = "Ninth Symposium on Information Theory in the Benelux", location = "Mierlo (NL), May 26-27, 1988", publisher = "Werkgemeenschap Informatie- en Communicatietheorie", address = "Enschede (NL)", year = "1988", pages = "121--128", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8801.html", ISBN = "90-71048-04-7", checked = "R. Moddemeijer, rudy at cs.rug.nl, 15 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 17 March 1999", abstract = "Mutual information is used in a model free and non-parametric general purpose method to define time-delays between stochastic signals. For each of the two stationary stochastic signals we define a past and a future by cutting both infinite sample sequences into two parts: the past and the future. The time-delay is considered to be the time-shift between the cutting moments for which the mutual information between both infinite length past vectors and both infinite lenght future vectors reaches a minimum. For stationary stochastic signals and under certain convergence conditions this mutual information posesses one unique minimum. We present some theoretical elaborations and discuss this method in relation to other methods.", } @TechReport{Moddemeijer:1988:BCF, author = "R. Moddemeijer", title = "Bias caused by finite resolution", institution = "University of Twente", address = "Enschede (NL)", year = "1988", keywords = "mutual information, bias, finite resolution", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @TechReport{Moddemeijer:1988:CSM, author = "R. Moddemeijer", title = "A curious signal model and its consequences for mutual information based delay estimation", institution = "University of Twente", address = "Enschede (NL)", number = "IR.080.87.49", year = "1988", keywords = "delay, estimation, mutual information", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @TechReport{Moddemeijer:1988:BMI, author = "R. Moddemeijer", title = "Bias of mutual information caused by the finite integration area", institution = "University of Twente", address = "Enschede (NL)", number = "IR.080.87.38", year = "1988", keywords = "mutual information, bias", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @TechReport{Moddemeijer:1988:VMI, author = "R. Moddemeijer", title = "The variance of the mutual information estimator", institution = "University of Twente", address = "Enschede (NL)", number = "AM.080.88.13", year = "1988", keywords = "mean, variance, estimator, mutual information, entropy, likelihood, dependent samples", checked = "R. Moddemeijer, rudy at cs.rug.nl, 18 March 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", } @PhdThesis{Moddemeijer:1989:DEA, author = "R. Moddemeijer", title = "Delay-Estimation with Application to Electroencephalograms in Epilepsy", school = "University of Twente", address = "Enschede (NL)", year = "1989", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8901.html", ISBN = "90-9002668-1", keywords = "epilepsy, diagnostics, information theory", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Delay-estimation has various applications in science; for example the tracing of submarines, the anylysis of electroencephalograms (EEG's) or the anylysis of seismological measurements. We concentrate on one application; the estimation of time-delays between electroecephalograms recorded during epileptic seizures. The purpose of this investigation is the location of the epileptogenic focus, the source of the epileptogenic activity, in focal epilesy. Because of insufficient knowledge of the medium, the brain, and the unreliability of the delay-estimation methods applid, we can only roughly determine the position of the focus. Our aim is to improve and to extend the delay-estimation methods applied. The first chapter of the thesis contains an introduction to epilepsy and EEG-analysis as weel as a motivation to estimate time-delays. Thereafter we present some delay-estimation methods. In the second chapter we extensively discuss the mutual information method to estimate time-delays caused by the finite propagation velocity of the epileptiform activity. This method resembles the cross-correlation method to estimate time-delays, only the cross-covariance is replaced by the mutual information. Several aspects of the mutual information method are discussed; a histogram based mutual information estimator and the bias as well as the variance of that estimator. Finally we apply this estimator to EEG's of an epilepsy patient and of a dog, epileptic by electrical stimulation.", } @Article{Moddemeijer:1989:EEM, author = "R. Moddemeijer", title = "On Estimation of Entropy and Mutual Information of Continuous Distributions", journal = "Signal Processing", volume = "16", number = "3", year = "1989", pages = "233--246", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8902.html", keywords = "mutual information, entropy, bias, variance, estimator, delay-estimation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Mutual information is uded in a procedure to estimate time-delays between recordings of electroencephalogram (EEG) signals originating from epileptic animals or patients. We present a simple and reliable histogram-based method to estimate mutual information. The accuracies of this mutual information estimator and of a similar entropy estimator are discussed. The bias and variance calculations presented can also be applied to discrete valued systems. Finally we present some simulation results, which are compared with earlier work.", } @InProceedings{Moddemeijer:1989:TCH, author = "R. Moddemeijer and E. W. Gr{\"o}neveld", title = "Testing composite hypotheses", editor = "A. M. et. el. Barb{\'e}", booktitle = "Tenth Symposium on Information Theory in the Benelux", address = "Houthalen (B)", month = may # " 25-26", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1989", pages = "133--138", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM8903.html", ISBN = "90-71048-05-5", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "We consider the estimation of parameters of a probability density function (pdf) of the observed vector variable $Z$ or rather the selection of one pdf from an a priori defined set of hpothetical pdf's of $Z$. It is assumed that the set set consistes of two subsets of pdf's $f_0(Z;P)$ and $f_1(Z;Q)$, $P$ and $Q$ are vectors of continuous parameters. The test of $f_1$ versus $f_0$ is then a test of composite hypotheses. The optimal parameters are $P^*$ and $Q^*$ maximizing the expectation of $\log f_0(Z;P)$ and $\log f_1(Z;Q)$. The subset in which this maximum is the largest is the subset to be selected. For a test based on $N$ observations we replace the expectation by the average; this average suffers from an $N$-dependent bias. We discuss ist (over)compensation. We relate it to the Akaike Information theoretic Criterion (AIC) and suggest an improved test to replace the latter.", } @InProceedings{Moddemeijer:1990:SLA, author = "R. Moddemeijer", title = "Sampling and linear algebra", editor = "J. C. A. van der Lubbe", booktitle = "Eleventh Symposium on Information Theory in the Benelux", address = "Noordwijkerhout (NL)", month = oct # " 25-26", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1990", pages = "118--125", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9001.html", ISBN = "90-71048-06-3", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Shannon, in his landmark publication, mentions the geometric representation of continuous time signals. In more recent literature linear algebra is hardly used to interpret the sampling of signals. We show thant sampling and the reconstruction of signals with a minimum mean square error corresponds with the computation of inner products of basis functions with a time-signal, an orthogonalisation and the reconstruction by a coefficient weighted sum of basis functions. The reconstruction error is caused by the projection of the signal onto a space determined by the basis functions. Shannon's sampling theorem corresponds with a special case determined by the basis functions which are shifted in time. Sampling, orthogonalisation and reconstruction can be done by (digital) linear filtering. These filters can be chosen causal, but they can not be all FIR-filters. The interpretation of sampling using linear algebra leads to alternative sampling procedures.", } @Article{Moddemeijer:1991:DPE, author = "R. Moddemeijer", title = "On the Determination of the Position of Extrema of Sampled Correlator", journal = "{IEEE} Transactions on Acoustics, Speech, and Signal Processing", volume = "39", number = "1", year = "1991", pages = "216--218", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9101.html", keywords = "delay, estimation, cross-covariance, mutual information, detection, sampling", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "The determination of the position of the extrumumn of a continuous correlator fuction from its samples, if the spectrum of the correlator is not band-limited, is still an unsolved problem. Searching for the position of the extremum by fitting a parabola through three samples around the extremum leads to clustering of the estimates around values corresponding with the sampling moments.", } @TechReport{Lankhorst:1992:AWC, author = "M. M. Lankhorst and R. Moddemeijer", title = "Automatic Word Categorization: An Information-theoretic Approach", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1992", note = "CS 9209", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9201.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9201.ps.gz", keywords = "linguistic categorization, information theory, mutual information", checked = "R. Moddemeijer, rudy at cs.rug.nl, 9 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "This paper presents a novel approach to the automatic categorization of words from raw data. We count occurrences of word pairs in text and use a hierarchical clustering technique on this frequency data to obtain a classification of words into linguistic categories. As a distance criterion in the clustering process, we use the loss of mutual information caused by combining two clusters into a single new cluster. The main advantage of such a method is the ability to construct linguistic categories that combine both syntactic and semantic/pragmatic factors, which may help in reducing the number of nonsensical analyses that a language processing system will produce. Results of the application of this method on letter data and on a word corpus are shown, which clearly demonstrate this blending of syntactic and semantic aspects that are related to their meanings. The method can form the basis of a system that uses a much finer categorization than is feasible using traditional grammer-based approaches. We plan to use it in a layered system of artificial neural networks that are trained to recognize higher-level consistuents.", } @InProceedings{Lankhorst:1993:AWC, author = "M. M. Lankhorst and R. Moddemeijer", title = "Automatic Word Categorization: An Information-theoretic Approach", editor = "K. A. Schouhamer Immink and P. G. M. Bot", booktitle = "Forteenth Symposium on Information Theory in the Benelux", address = "Veldhoven (NL)", month = may # " 17-18", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1993", pages = "62--69", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9301.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9301.ps.gz", ISBN = "90-71048-09-8", keywords = "linguistic categorization, information theory, mutual information", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "This paper presents a novel approach to the automatic categorization of words from raw dara. We count occurrences of word pairs in text and use a hierarchical clustering technique on this frequency data to obtain a classification of words into linguistic categories. As a distance criterion in the clustering process, we use the loss of mutual information caused by combining two clusters into a single new cluster. With this method, words are not only classified on basis of their syntactic categories, but also with respect to aspects that are related to meanings. The method can form the basis of a system that uses a much finer categorization of words than is feasible using traditional grammaer-based approaches. We plan to use it in a layered system of artificial neural networks that are trained to recognize higher-level constituents.", } @Article{Moddemeijer:1999:SEV, author = "R. Moddemeijer", title = "A statistic to estimate the variance of the histogram based mutual information estimator based on dependent pairs of observations", journal = "Signal Processing", volume = "75", number = "1", year = "1999", pages = "51--63", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM971.html", URL = "http://www.elsevier.com/cgi-bin/cas/tree/store/sigpro/cas_sub/browse/browse.cgi?year=1999&volume=75&issue=1&aid=1370", URL = "http://www.elsevier.com/cas/tree/store/sigpro/sub/1999/75/1/1370.pdf", URL = "http://www.cs.rug.nl/~rudy/papers/documents/RM9701.ps.gz", keywords = "sample mean, variance, statistic, mutual information, entropy, likelihood, dependent samples", checked = "R. Moddemeijer, rudy at cs.rug.nl, 26 August 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "In the case of two signals with independent pairs of observations $(x_n,y_n)$ a statistic to estimate the variance of the mutual information estimator has been derived earlier. We present such a statistic for dependent pairs. To derive this statistic it is necessary to avail of a reliable statistic to estimate the variance of the sample mean in case of dependent observations. We derive and discuss this statistic and a statistic to estimate the variance of the mutual information estimator. These statistics are verified by simulations.", } @Article{Moddemeijer:1997:CISa, author = "R. Moddemeijer", title = "On the convergence of the iterative solution of the likelihood equations", journal = "Computational Statistics and Data Analysis", volume = "???", number = "???", year = "???", pages = "???", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9702.html", keywords = "Likelihood Equations, Convergence, Maximum likelihood estimation, Simulation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 26 August 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "To determine the maximum likelihood estimate in case of the iterative solution of the likelihood equations we need a convergence criterion. Usually numerically motivated convergence criteria are used; we propose a statistically motivated convergence criterion. Our criterion reduces the number of iterations tremendously. The iterative algorithm to solve the equations is known to be unstable in the neighborhood of the exact solution. Our method avoids this numerical unstable region. The theory is validated by simulations.", } @TechReport{Moddemeijer:1997:CISb, author = "R. Moddemeijer", title = "On the convergence of the iterative solution of the likelihood equations", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "CS-R9711", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9703.html", keywords = "Likelihood Equations, Convergence, Maximum likelihood estimation, Simulation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "To determine the maximum likelihood estimate in case of the iterative solution of the likelihood equations we need a convergence criterion. Usually numerical convergence criteria have been used; we propose a statistical convergence criterion. Our criterion reduces the number of iterations tremendously. The iterative algorithm to solve the equations is known to be unstable in the neighborhood of the exact solution. Our method avoids this numerical unstable region. The theory is validated by simulations.", } @TechReport{Moddemeijer:1997:TCHa, author = "R. Moddemeijer", title = "Testing composite hypotheses; the {Akaike}-criterion revised", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "CS-R9707", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9704.html", keywords = "AIC, Akaike criterion, composite hypothesis, entropy, maximum likelihood, mutual information, Neyman-Pearson", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Akaike's criterion is often used to test composite hypotheses. Objections are formulated against Akaike's criterion and some modifications are proposed such that the criterion becomes consistent. A method is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). For this purpose the method of maximum likelihood to estimate probability density functions (not parameters) is studied. As a result the \emph{single observation log likelihood} is presented. The sequence of the single observation log likelihoods is a stochastic signal to which signal processing can be applied. This is a fruitful concept which opens a new field of research. The presented theory is verified by simulations.", } @TechReport{Moddemeijer:1997:VMI, author = "R. Moddemeijer", title = "The variance of the mutual information estimator", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "CS-R9701", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9705.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9705.ps.gz", keywords = "sample mean, variance, statistic, mutual information, entropy, likelihood, dependent samples", checked = "R. Moddemeijer, rudy at cs.rug.nl, 9 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "In the case of two signals with independent pairs of observations $(x_n,y_n)$ a statistic to estimate the variance of the mutual information estimator has been derived earlier. We present such a statistic for dependent pairs. To derive this statistic it is necessary to avail of a reliable statistic to estimate the variance of the sample mean in case of dependent observations. We derive and discuss this statistic and a statistic to estimate the variance of the mutual information estimator. These statistics are verified by simulations.", } @InProceedings{Moddemeijer:1998:TCHa, author = "R. Moddemeijer", title = "Testing composite hypotheses applied to {AR} order estimation; the {Akaike}-criterion revised", booktitle = "Signal Processing Symposium (SPS '98)", address = "Leuven (B)", publisher = "{IEEE} Benelux Signal Processing Chapter", month = Mar # " 26-27", year = "1998", pages = "135--138", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9803.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/posters/RM9803.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9803.ps.gz", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Akaike's criterion is used to test composite hypotheses; for example to determine the order of AR-models. A modification is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). The presented theory is applied to AR-order estimation and verified by simulations. The experimental results are so good that we consider the AR-order estimation problem as solved.", } @Unpublished{Moddemeijer:1997:TCHb, author = "R. Moddemeijer", title = "Testing composite hypotheses applied to {AR} order estimation; the {Akaike}-criterion revised", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "Submitted to {IEEE} Transactions on Signal Processing", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9804.html", keywords = "AIC, Akaike criterion, AR, ARMA, autoregressive processes, composite hypothesis, entropy, maximum likelihood, model order, mutual information, Neyman-Pearson, system identification, time series analysis", checked = "R. Moddemeijer, rudy at cs.rug.nl, 17 May 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Akaike's criterion is often used to test composite hypotheses; for example to determine the order of a priori unknown Auto-Regressive and/or Moving Average models. Objections are formulated against Akaike's criterion and some modifications are proposed such that the criterion becomes consistent. A method is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). For this purpose the method of maximum likelihood to estimate probability density functions (not parameters) is studied. As a result the \emph{single observation log likelihood} is presented. The sequence of the single observation log likelihoods is a stochastic signal to which signal processing can be applied. This is a fruitful concept which opens a new field of research. The presented theory is applied to AR-order estimation and verified by simulations. The experimental results are so good that we consider the AR-order estimation problem as solved.", } @Unpublished{Moddemeijer:1998:AIC, author = "R. Moddemeijer", title = "Application of information criteria to {AR} order estimation", year = "1998", note = "Resubmitted as Technical Paper for publication in {IEEE} Transactions on Automatic Control", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9805.html", keywords = "AIC, Akaike criterion, AR, ARMA, autoregressive processes, composite hypothesis, entropy, GIC, maximum likelihood, model order, system identification, time series analysis", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Information criteria, like the Akaike criterion, can be applied to AR order estimations. In recent research we have indicated that the search strategy by the application of information criteria to Auto-Regressive (AR) order estimation is essential. There are essentially two different strategies: search the optimal order by the first local minimum of the criterion or search the order by the global minimum given a maximum candidate order. Although the second strategy is mostly used, we will argue and verify by simulations that the first strategy is correct and will give significantly better results.", } @InProceedings{Moddemeijer:1998:TCHb, author = "R. Moddemeijer", title = "Testing composite hypotheses applied to {AR} order estimation; the {Akaike}-criterion revised", editor = "P. H. N. de With and M. van der Schaar-Mitrea", booktitle = "Nineteenth Symposium on Information Theory in the Benelux", address = "Veldhoven (NL)", month = may # " 28-29", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede, (NL)", year = "1998", pages = "149--156", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9806.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/slides/RM9806.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9806.ps.gz", ISBN = "90-71048-13-6", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Akaike's criterion is used to test composite hypotheses; for example to determine the order of AR models. A modification is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). The presented theory is applied to AR order estimation and verified by simulations. The experimental results are so good that we consider the AR order estimation problem as solved.", } @Unpublished{Moddemeijer:1997:TCHc, author = "R. Moddemeijer", title = "Testing composite hypotheses; the {Akaike}-criterion revised", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "Rejected for publication, no plans for publication", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9808.html", keywords = "AIC, Akaike criterion, composite hypothesis, entropy, maximum likelihood, mutual information, Neyman-Pearson", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "Akaike's criterion is often used to test composite hypotheses; for example to determine the order of a priori unknown Auto-Regressive and/or Moving Average models. Objections are formulated against Akaike's criterion and some modifications are proposed such that the criterion becomes consistent. A method is presented to test composite hypotheses given an upper-bound on the error of the first kind (Neyman-Pearson). For this purpose the method of maximum likelihood to estimate probability density functions (not parameters) is studied. As a result the single observation log likelihood is presented. The sequence of the single observation log likelihoods is a stochastic signal to which signal processing can be applied. This is a fruitful concept which opens a new field of research. The presented theory is verified by simulations.", } @Unpublished{Moddemeijer:1999:EAS, author = "R. Moddemeijer", title = "An efficient algorithm for selecting optimal configurations of {AR}-coefficients", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1999", note = "Submitted for publication in {IEEE} Transactions on Signal Processing", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9901.html", keywords = "AIC, Akaike criterion, AR, ARMA, autoregressive processes, composite hypothesis, entropy, maximum likelihood, model order, mutual information, Neyman-Pearson, system identification, time series analysis", checked = "R. Moddemeijer, rudy at cs.rug.nl, 1 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "There exists an essential difference between the correct Auto Regressive (AR) model and the optimal AR-model. We try to find an optimal model balancing between flexibility, using many AR-parameters, and low variance, using only a few AR-parameters. We select an optimal AR-parameter configuration consisting of zero and non-zero parameters given a maximum AR-order. This optimal configuration will be selected using a Modified Information Criterion (MIC) which is closely related to Akaike's criterion (AIC). This MIC allows an a priori selection of the probability of estimating too many parameters. We present the theoretical foundation of the method and verify this method by simulations. The method is based on pivoting the Hessian matrix by Gau\ss-Jordan pivots. As a result we can now select an optimal parameter configuration with an a priori probability of selecting a configuration with a too large number of parameters given an a priori selected maximum AR-order.", } @InProceedings{Moddemeijer:1999:EASb, author = "R. Moddemeijer", title = "An efficient algorithm for selecting optimal configurations of {AR}-coefficients", editor = "A. Barb\'e et. al.", booktitle = "Twentieth Symposium on Information Theory in the Benelux", address = "Haasrode (B)", month = may # " 27-28", publisher = "Werkgemeenschap Informatie- en Communicatietheorie, Enschede (NL)", year = "1999", pages = "189--196", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9902.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/slides/RM9902.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9902.ps.gz", ISBN = "90-71048-14-4", checked = "R. Moddemeijer, rudy at cs.rug.nl, 31 May 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 17 March 1999", abstract = "There exists an essential difference between the correct Auto Regressive (AR) model and the optimal AR-model. We try to find an optimal model balancing between flexibility, using many AR-parameters, and low variance, using only a few AR-parameters. We select an optimal AR-parameter configuration consisting of zero and non-zero parameters given a maximum AR-order. This optimal configuration will be selected using a Modified Information Criterion (MIC) which is closely related to Akaike's criterion (AIC). This MIC allows an a priori selection of the probability of estimating too many parameters. We present the method and a verification by simulations. The method is based on pivoting the Hessian matrix by Gauss-Jordan pivots. As a result we can now select an optimal parameter configuration with an a priori probability of selecting a configuration with a too large number of parameters given an a priori selected maximum AR-order.", } @Unpublished{Moddemeijer:1999:AOE, author = "R. Moddemeijer", title = "{AR} order estimation by testing sets using the Modified Information Criterion", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1999", note = "Submitted to Automatica, February 1999", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9903.html", keywords = "AIC, Akaike criterion, AR, ARMA, autoregressive processes, composite hypothesis, entropy, maximum likelihood, model order, mutual information, Neyman-Pearson, system identification, time series analysis", checked = "R. Moddemeijer, rudy at cs.rug.nl, 17 May 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "The Modified Information Criterion (MIC) is an Akaike-like criterion which allows performance control by means of a simple a priori defined parameter, the upper-bound on the error of the first kind (false alarm probability). The criterion MIC is for example used to estimate the order of Auto-Regressive (AR) processes. The criterion can only be used to test pairs of composite hypotheses; in an AR-order estimation this leads to sequential testing. Usually the Akaike criterion is used to test sets of composite hypotheses. The difference between sequential and set testing corresponds with the difference between searching the first local and the global minimum of the Akaike criterion. We extend the criterion MIC to testing a composite null-hypothesis versus a set of composite alternative hypotheses; these alternative hypotheses form a sequence where every element introduces one additional parameter. The theory is verified by simulations and is compared with the Akaike criterion used in sequential and set testing. Due to the excellent correspondence between the theory and the experimental results we consider the AR-model order estimation problem for low order AR-processes with Gaussian white noise as solved.", } @InProceedings{Nijhuis:1998:DPC, author = "J. A. G. Nijhuis and M. H. ter Brugge and R. Moddemeijer and L. Spaanenburg", title = "Designing Preselective Classifiers", booktitle = "European Conference on Circuit Theory and Design (ECCTD '99)", address = "Stresa (I)", month = Aug # " 29-" # Sep # " 2", year = "1999", pages = "859--862", editor = "C. Beccari et. al.", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9904.html", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 September 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 19 April 1999", abstract = "High-performance classifiers derive from an hierarchical scheme to balance accuracy and precision. From practice in intelligent license-plate readingwe discuss how the accuracy can be raised using a heterogeneous set of intelligent modules. Further we introduce an extension of the Akaike theorem to set the decision threshold for optimal precision. This allows for a real-time reading that has identified more than 85\% of the passing cars with a 0\% false acceptance during 2 weeks in March 1999 on a highway near Utrecht (The Netherlands)", } @Misc{Moddemeijer:1999:BSI, author = "R. Moddemeijer", title = "Bibliography of the Symposia on Information Theory in the Benelux", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1999", URL = "http://liinwww.ira.uka.de/bibliography/Theory/WICsymp.html", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9905.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/WICsymp.bib", keywords = "information theory, communication theory, coding, entropy, cryptography, estimation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 16 April 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 16 March 1999", abstract = "The Symposia on Information Theory in the Benelux are yearly conferences on information theory organized by the Werkgemeenschap voor Informatie- en Communictietheorie (WIC) in cooperation with the IEEE Benelux Information Theory Chapter. The WIC is the Benelux information theory society.", howpublished = "on-line document, accessible by FTP", } @Misc{Moddemeijer:1999:BWI, author = "R. Moddemeijer", title = "Bibliography of the Werkgemeenschap Informatie- en Communicatietheorie", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1999", URL = "http://liinwww.ira.uka.de/bibliography/Theory/WICmember.html", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9906.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/WICmember.bib", keywords = "information theory, communication theory, coding, entropy, cryptography, estimation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 26 May 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 16 March 1999", abstract = "The Werkgemeenschap voor Informatie- en Communictietheorie is the Benelux information theory society. This society publishes a newsletter, the Informant, in which a part of this list of publications of members was published.", howpublished = "on-line document, accessible by FTP", } @Unpublished{Moddemeijer:1999:SOS, author = "R. Moddemeijer", title = "Selecting an optimal set of parameters using an {Akaike} like criterion", year = "1999", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9908.html", checked = "R. Moddemeijer, rudy at cs.rug.nl, 9 September 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 26 April 1999", abstract = "The selection of an optimal set of parameters from a larger one is a well known identification problem in classification or clustering algorithms. The Akaike criterion has been developed to estimate the (Markov) order in auto regressive models. This criterion, which by itself extends the maximum likelihood method to test composite hypotheses, is replaced by the \emph{Modified Information Criterion} (MIC). This criterion balances bias caused insufficient modeling and the additional variance caused by superfluous parameters. Using this criterion the probability of selecting a model with too many parameters can, without the need of extensively evaluating the bias/variance syndrome, a priori be chosen.", } @InProceedings{Moddemeijer:1999:TCH, author = "R. Moddemeijer", title = "Testing composite hypotheses applied to {AR}-order estimation; the {Akaike}-criterion revised", booktitle = "European Conference on Circuit Theory and Design (ECCTD '99)", address = "Stresa (I)", month = aug # " 29-" # sep # " 2", year = "1999", pages = "723--726", editor = "C. Beccari et. al.", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9909.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/slides/RM9909.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9909.ps.gz", checked = "R. Moddemeijer, rudy at cs.rug.nl, 6 September 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 19 April 1999", abstract = "Akaike's criterion is often used to test composite hypotheses; for example to determine the order of a priori unknown Auto-Regressive (AR) processes. Objections are formulated against Akaike's criterion and some modifications are proposed. The application of the theory leads to a general technique for AR-model order estimation based on testing composite hypotheses. This technique allows performance control by means of a simple parameter, the upper-bound on the probability of estimating a too high AR-order; the \emph{false alarm probability} (FAP). The presented simulations and the theoretical elaboration improve the understanding of the problems and limitations of techniques based on the Akaike criterion. Due to the excellent correspondence between the theory and the experimental results we consider the in AR-model order estimation problem for low order AR-model with Gaussian white noise as solved", } @Unpublished{Moddemeijer:1997:CISa, author = "R. Moddemeijer", title = "On the convergence of the iterative solution of the likelihood equations", institution = "University of Groningen, Department of Computing Science", address = "P.O. Box 800, NL-9700 AV Groningen, The Netherlands", year = "1997", note = "Submitted to Technometrics", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9702.html", keywords = "Likelihood Equations, Convergence, Maximum likelihood estimation, Simulation", checked = "R. Moddemeijer, rudy at cs.rug.nl, 17 May 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 15 March 1999", abstract = "To determine the maximum likelihood estimate in case of the iterative solution of the likelihood equations we need a convergence criterion. Usually numerically motivated convergence criteria are used; we propose a statistically motivated convergence criterion. Our criterion reduces the number of iterations tremendously. The iterative algorithm to solve the equations is known to be unstable in the neighborhood of the exact solution. Our method avoids this numerical unstable region. The theory is validated by simulations.", } @InProceedings{Moddemeijer:1999:SSS, author = "R. Moddemeijer and L. Spaanenburg", title = "Selection of sufficient stochastic data-models applied to modeling", editor = "J. P. Veen", booktitle = "Proceedings of the 10th workshop on Circuits, Systems and Signal Processing ({IEEE}/{ProRISC99})", address = "Mierlo (NL)", month = nov # " 25-26", publisher = "{STW} Technology Foundation, Utrecht (NL)", year = "1999", pages = "307--316", ISBN = "90-73461-18-9", URL = "http://www.cs.rug.nl/~rudy/papers/abstracts/RM9912.html", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/posters/RM9912.ps.gz", URL = "ftp://ftp.cs.rug.nl/pub/users/rudy/documents/RM9912.ps.gz", checked = "R. Moddemeijer, rudy at cs.rug.nl, 29 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 16 September 1999", note = "Published on CD-Rom", abstract = "The constructive derivation of the sufficient model for analysis and design of an electronic circuit assumes the availability of a rich set of alternatives. Rather than to iterate the selection of a single model by trial-and-error, we advocate here the structured elimination through the application of log-likelihood statistics. This method was originally developed for auto-regressive (AR) order estimation. The generic architectural model is validated once to establish the desired balance between model bias caused by insufficient modeling and additional variance caused by superfluous parameters. The result is one or more functionally indistinguishable model implementations. From restrictions on the scarce availability of realization resources, the most suitable model for design and analysis can finally be picked. This top-down style of model derivation is illustrated in the analysis of an analogue integrated circuit. It shows how already from a limited set of experimental data a sufficient model can be pinpointed. This allows to reduce the long and painstaking model derivation for new devices and macro-models to a matter of CPU minutes.", } @InBook{Moddemeijer:1999:SSSa, author = "R. Moddemeijer", title = "Selection of sufficient stochastic data-models applied to {AR} modeling", editor = "H. Ros and J. P. Veen", booktitle = "Abstracts of the {SAFE99} & {ProRISC99} workshops", address = "Mierlo (NL)", month = nov # " 24-26", publisher = "{STW} Technology Foundation, Utrecht (NL)", year = "1999", pages = "108", checked = "R. Moddemeijer, rudy at cs.rug.nl, 23 November 1999", entered = "R. Moddemeijer, rudy at cs.rug.nl, 23 November 1999", ISBN = "90-73461-17-0", }