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Journal ArticleDOI

Probabilistic neural networks

Donald F. Specht
- 01 Jan 1990 - 
- Vol. 3, Iss: 1, pp 109-118
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.

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Citations
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Journal ArticleDOI

Flexible software for condition monitoring, incorporating novelty detection and diagnostics

TL;DR: The development of a flexible software solution for condition monitoring, novelty identification and machinery diagnostics, which can easily be customised to a wide range of monitoring scenarios is presented.
Proceedings ArticleDOI

PNN for EEG-based Emotion Recognition

TL;DR: In this paper, a probabilistic neural network (PNN) was employed to recognize emotions elicited by watching music videos from scalp EEG, and the results showed that the mean classification accuracy of PNN is 81.21% for valence(≥5 and <5) and 81.26% for arousal(≩5 and >5) across 32 subjects, similar with the results of SVM.
Journal ArticleDOI

Estimation and generation of training patterns for control chart pattern recognition

TL;DR: This paper presents a scheme to generate training patterns that addresses the issue of diversity and comparability and comprises change point detection and mean change categorisation methods that implement nonlinear models (NLMs) for estimating abnormal pattern parameters.
Journal ArticleDOI

Rare earth elements minimal harvest year variation facilitates robust geographical origin discrimination: The case of PDO “Fava Santorinis”

TL;DR: The results show that seasonal patterns can occur in the elemental composition of "Fava Santorinis", probably reflecting seasonality of climate.
Journal ArticleDOI

Rolling Bearing Fault Diagnosis Based on CEEMDAN and Refined Composite Multiscale Fuzzy Entropy

TL;DR: In this paper, a rolling bearing fault diagnosis method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), refined composite multiscale fuzzy entropy (RCMFE), Laplace score (LS), and the particle swarm optimization-probabilistic neural network (PSO-PNN) was proposed.
References
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Journal ArticleDOI

Nearest neighbor pattern classification

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.

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.