A neural network approach to statistical pattern classification by 'semiparametric' estimation of probability density functions
IEEE Transactions on Neural NetworksPublished 1 May 1991
Hans G. C. Tråvén
Citations192
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A method for designing near-optimal nonlinear classifiers, based on a self-organizing technique for estimating probability density functions when only weak assumptions are made about the densities, is described.
Abstract
A method for designing near-optimal nonlinear classifiers, based on a self-organizing technique for estimating probability density functions when only weak assumptions are made about the densities, is described. The method avoids disadvantages of other existing methods by parametrizing a set of component densities from which the actual densities are constructed. The parameters of the component densities are optimized by a self-organizing algorithm, reducing to a minimum the labeling of design samples. All the required computations are realized with the simple sum-of-product units commonly used in connectionist models. The density approximations produced by the method are illustrated in two dimensions for a multispectral image classification task. The practical use of the method is illustrated by a small speech recognition problem. Related issues of invariant projections, cross-class pooling of data, and subspace partitioning are discussed.
Keywords
Computer Science
Munich Personal RePEc Archive (Ludwig Maximilian University of Munich)Some methods for classification and analysis of multivariate observations
22,787 Citations1967James B. MacQueen
The MIT Press eBooksParallel Distributed Processing
15,227 Citations1986David E. Rumelhart, James L. McClelland +1 more
The Annals of Mathematical StatisticsOn Estimation of a Probability Density Function and Mode
10,504 Citations1962Emanuel Parzen
Springer series in information sciencesSelf-Organization and Associative Memory
8,770 Citations1989Teuvo Kohonen
Neural ComputationFast Learning in Networks of Locally-Tuned Processing Units
4,219 Citations1989John Moody, Christian J. Darken
This work proposes a network architecture which uses a single internal layer of locally-tuned processing units to learn both classification tasks and real-valued function approximations (Moody and Darken 1988).
Neural NetworksProbabilistic neural networks
3,738 Citations1990Donald F. Specht
A probabilistic neural network that can compute nonlinear decision boundaries which approach the Bayes optimal is formed, and a fourlayer neural network of the type proposed can map any input pattern to any number of classifications.
Perceptrons: an introduction to computational geometry
3,308 Citations1969Marvin Minsky, Seymour Papert
Journal of NeuroscienceTheory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex
2,950 Citations1982EL Bienenstock, L N Cooper +1 more
The development of stimulus selectivity in the primary sensory cortex of higher vertebrates is considered in a general mathematical framework and a synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete.
Biological CyberneticsAdaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors
1,916 Citations1976Stephen Grossberg
It is shown how experience can retune feature detectors to respond to a prescribed convex set of spatial patterns, and a classification of adult feature detector properties in terms of a small number of functional principles is suggested.
Philosophical Transactions of the Royal Society of London (A )III. Contributions to the mathematical theory of evolution
1,528 Citations1894Karl Pearson
KybernetikSelf-organization of orientation sensitive cells in the striate cortex
1,481 Citations1973Chr. von der Malsburg
A nerve net model for the visual cortex of higher vertebrates is presented and a simple learning procedure is shown to be sufficient for the organization of some essential functional properties of single units.
IEEE Transactions on Automatic ControlNonlinear Bayesian estimation using Gaussian sum approximations
1,229 Citations1972D. Alspach, H.W. Sorenson
In this paper an approximation that permits the explicit calculation of the a posteriori density from the Bayesian recursion relations is discussed and applied to the solution of the nonlinear filtering problem.
AutomaticaRecursive bayesian estimation using gaussian sums
948 Citations1971H.W. Sorenson, D. Alspach
A density approximation involving convex combinations of gaussian density functions is introduced and proposed as a meaningful way of circumventing the difficulties encountered in evaluating these relations and in using the resulting densities to determine specific estimation policies.
Proceedings of the IEEEVector quantization in speech coding
845 Citations1985J. Makhoul, S. Roucos +1 more
This tutorial review presents the basic concepts employed in vector quantization and gives a realistic assessment of its benefits and costs when compared to scalar quantization, and focuses primarily on the coding of speech signals and parameters.
Multivariate Behavioral ResearchPATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSIS
604 Citations1970J. H. Wolfe
The maximum-likelihood theory and numerical solution techniques are developed for a fairly general class of distributions and the feasibility of the procedures is demonstrated by two examples of computer solutions for normal mixture models of the Fisher Iris data and of artify generated clusters with unequal covariance matrices.
Neural NetworksA time-delay neural network architecture for isolated word recognition
587 Citations1990Kevin Lang, Alex Waibel +1 more
A translation-invariant back-propagation network is described that performs better than a sophisticated continuous acoustic parameter hidden Markov model on a noisy, 100-speaker confusable vocabulary isolated word recognition task.
IEEE Transactions on Neural NetworksProbabilistic neural networks and the polynomial Adaline as complementary techniques for classification
581 Citations1990Donald F. Specht
Two methods for classification based on the Bayes strategy and nonparametric estimators for probability density functions are reviewed and the polynomial equivalent can be found.
Neural ComputationReview of Neural Networks for Speech Recognition
480 Citations1989Richard P. Lippmann
Further work is necessary for large-vocabulary continuous-speech problems, to develop training algorithms that progressively build internal word models, and to develop compact VLSI neural net hardware.
TechnometricsEstimation of Parameters for a Mixture of Normal Distributions
474 Citations1966Victor Hasselblad
Statistical pattern recognition with neural networks: benchmarking studies.
404 Citations1988Teuvo Kohonen, G. Barna +1 more
IEEE International Conference on Neural NetworksStatistical pattern recognition with neural networks: benchmarking studies
349 Citations1988Kohonen, Barna +1 more
Three basic types of neural-like networks, backpropagation network, Boltzmann machine, and learning vector quantization, were applied to two representative artificial statistical pattern recognition tasks, each with varying dimensionality.
Elsevier eBooksPhoneme Recognition Using Time-Delay Neural Networks
301 Citations1990Alexander Waibel, Toshiyuki Hanazawa +3 more
TechnometricsEstimation of Parameters for a Mixture of Normal Distributions
146 Citations1966Victor Hasselblad
IEEE International Conference on Neural NetworksThe subspace learning algorithm as a formalism for pattern recognition and neural networks
37 Citations1988Oja, Kohonen
The subspace method has been developed for a practical pattern-recognition algorithm and some recent results on image analysis are given.
IEEE Transactions on Information TheoryOptimal unsupervised learning multicategory dependent hypotheses pattern recognition
20 Citations1968C. Hilborn, D.G. Lainiotis
The main contributions of this paper are the extension of previous investigations of the unsupervised parametric pattern recognition problem to include cases where both constant and time-varying unknown parameter vectors are simultaneously present and the removal of the assumption of statistical independence between hypotheses for the sequence of observations.
Auditory models in isolated word recognition
10 Citations2005Margareta R. A. Blomberg, Rolf Carlson +2 more
A straightforward isolated word recognition system has been used to test different auditory models in acoustic front end processing, and the results indicate that the performance of the models decreases as they become more complex.