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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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A fuzzy system for concrete bridge damage diagnosis

TL;DR: A fuzzy rule-based inference system for bridge damage diagnosis and prediction which aims to provide bridge designers with valuable information about the impacts of design factors on bridge deterioration is presented.
Journal ArticleDOI

Empirical Wavelet Transform Based Features for Classification of Parkinson’s Disease Severity

TL;DR: Experimental results demonstrated that the proposed approach had the ability to differentiate PD from non-PD subjects, including their severity level – with classification accuracies of more than 90% using EWT/EWPT-ELM based on signals from motion and audio sensors respectively.
Journal ArticleDOI

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

TL;DR: An automated dry AMD detection system using various entropies, Higher Order Spectra bispectra features, Fractional Dimension features, and Gabor wavelet features extracted from greyscale fundus images can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.
Journal ArticleDOI

Combination of hyperbolic functions for multimodal biometrics data fusion

TL;DR: This work proposes a network model to generate different combinations of the hyperbolic functions to achieve some approximation and classification properties to circumvent the iterative training problem as seen in neural network learning.

IJCSI Publicity Board 2010

TL;DR: This paper presents a systematic analysis of a variety of different ad hoc network topologies in terms of node placement, node mobility and routing protocols through several simulated scenarios.
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.