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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

A three-phase NPC grid-connected inverter for photovoltaic applications using neural network MPPT

TL;DR: A comparative study of the performances of a photovoltaic system connected to the grid using two different inverters namely the two-level inverter and the three-level Neutral Point Clamped (NPC) Voltage Source Inverter (VSI).
Journal ArticleDOI

Decision support systems for police: lessons from the application of data mining techniques to soft forensic evidence

TL;DR: It is argued that computer science technologies which can support criminal investigations are wide ranging and include geographical information systems displays, clustering and link analysis algorithms and the more complex use of data mining technology for profiling crimes or offenders and matching and predicting crimes.
Journal ArticleDOI

Heterogeneous fault diagnosis for wireless sensor networks

TL;DR: The proposed protocol consists of three phases, such as clustering phase, fault detection phase, and fault classification phase to diagnose the heterogeneous faulty nodes in the wireless sensor networks.
Patent

System and method for pain detection and computation of a pain quantification index

TL;DR: In this paper, a method of detecting pain in subject comprises of generating brain wave data based on brain wave activity of subject and comparing the brain-wave data to reference data to generate result data.
Journal ArticleDOI

Diagnosis of diabetic retinopathy using machine learning techniques

TL;DR: To diagnose diabetic retinopathy, three models like Probabilistic Neural network (PNN), Bayesian Classification and Support vector machine (SVM) are described and their performances are compared and it is inferred that the SVM model outperforms all other models.
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.