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
More filters
Journal ArticleDOI
Capturing the volatility smile of options on high-tech stocks—A combined GARCH-neural network approach
Gunter Meissner,Noriko Kawano +1 more
TL;DR: In this paper, a modified version of the standard GARCH equation is used to model historical volatility and a neural network is used for each individual high-tech stock to adapt to the market inherent volatility distortion.
Proceedings ArticleDOI
Terrain surface classification for autonomous ground vehicles using a 2D laser stripe-based structured light sensor
TL;DR: This paper considers vision-based terrain surface classification for the path directly in front of the vehicle, using a laser stripe-based structured light sensor, which uses a laser in conjunction with a camera, and hence can work at night.
Book ChapterDOI
Probabilistic neural networks: A brief overview of theory, implementation, and application
TL;DR: This chapter takes a look at the fundamental mathematics behind the modern PNNs, their application, and approaches that address some practical issues that come with them.
Journal ArticleDOI
One-shot Cluster-Based Approach for the Detection of COVID-19 from Chest X-ray Images.
TL;DR: In this paper, a cluster-based one-shot learning is introduced for detecting COVID-19 from chest X-ray images, which has an advantage of learning from a few samples against learning from many samples in case of deep leaning architectures.
Book ChapterDOI
Neural Networks in Multiple Classifier Systems for Remote-Sensing Image Classification
TL;DR: This chapter surveys key neural and non-neural methods in this area and develops some new ones including traditional feed-forward neural networks, probabilistic neuralnetworks and radial-basis nets.
References
More filters
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.
Journal ArticleDOI