Journal ArticleDOI
Probabilistic neural networks
TLDR
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.About:
This article is published in Neural Networks.The article was published on 1990-01-01. It has received 3772 citations till now. The article focuses on the topics: Probabilistic neural network & Activation function.read more
Citations
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Modeling energy consumption in residential buildings: A bottom-up analysis based on occupant behavior pattern clustering and stochastic simulation
TL;DR: In this paper, the authors proposed to identify and classify occupants' behavior with direct energy consumption outcomes and energy time use data through unsupervised clustering, based on the American Time Use Survey (ATUS), the proposed approach integrates k-modes clustering and demographic-based probability neural networks and identifies 10 distinctive behavior patterns.
Journal ArticleDOI
Classification of olive oils using high throughput flow 1H NMR fingerprinting with principal component analysis, linear discriminant analysis and probabilistic neural networks
TL;DR: In this article, a combination of 1H NMR fingerprinting with multivariate analysis provides an original approach to study the profile of olive oil in relation to its geographical origin and processing.
Journal ArticleDOI
Fuzzy basis functions: comparisons with other basis functions
Hyun Mun Kim,Jerry M. Mendel +1 more
TL;DR: A FBF network is compared with a radial basis function (RBF) network from the viewpoint of function approximation, and its architectural interrelationships are discussed.
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Application of neural networks and sensitivity analysis to improved prediction of trauma survival.
TL;DR: A novel form of sensitivity analysis is proposed, which is simpler to apply than existing techniques, and can be used for both numeric and nominal input variables, and applied to the audit survival problem.
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Artificial neural networks and genetic algorithm for bearing fault detection
TL;DR: A study is presented to compare the performance of three types of artificial neural network, namely, multi layer perceptron (MLP), radial basis function (RBF) network and probabilistic neural network (PNN), for bearing fault detection.
References
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Journal ArticleDOI
Nearest neighbor pattern classification
Thomas M. Cover,Peter E. Hart +1 more
TL;DR: The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points, so it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.
Journal ArticleDOI
On Estimation of a Probability Density Function and Mode
TL;DR: In this paper, the problem of the estimation of a probability density function and of determining the mode of the probability function is discussed. Only estimates which are consistent and asymptotically normal are constructed.
Book
Introduction to the Theory of Statistics
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
Journal ArticleDOI
Introduction to the Theory of Statistics.
Jacob Wolfowitz,A. M. Mood +1 more
TL;DR: In this article, a tabular summary of parametric families of distributions is presented, along with a parametric point estimation method and a nonparametric interval estimation method for point estimation.
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