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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

Ultrasonic image analysis for liver diagnosis

TL;DR: A new ultrasonic image analysis system that can be utilized as an effective tool in classifying liver states as normal, hepatitis, or liver cirrhosis is proposed.
Journal ArticleDOI

Machine Intelligence in Healthcare and Medical Cyber Physical Systems: A Survey

TL;DR: A survey of machine intelligence algorithms within the context of healthcare applications is provided and includes a comprehensive list of the most commonly used computational models and algorithms.
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BA-PNN-based methods for power transformer fault diagnosis

TL;DR: A machine learning-based approach to power transformer fault diagnosis based on dissolved gas analysis (DGA), a bat algorithm (BA), optimizing the probabilistic neural network (PNN), demonstrating that BA is an effective algorithm for optimizing PNN smooth factor and BA-PNN can improve the fault diagnosis performance.
Journal ArticleDOI

Intelligent tool path generation for milling of free surfaces using neural networks

TL;DR: In this paper, the authors presented how with the help of Artificial Neural Network (ANN), the prediction of milling tool-path strategy could be made in order to establish which milling path strategy or their sequence will show the best results (will be the most appropriate) at free surface machining, according to set technological aim.
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Suspension system state estimation using adaptive Kalman filtering based on road classification

TL;DR: In this paper, a new method to solve the problem of suspension system state estimation using a Kalman Filter (KF) under various road conditions was proposed, where the influence of the system process noise variance and measurement noise covariance on the estimation accuracy of the KF was analyzed.
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.
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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.