概率神经网络 Resources

Showing items tagged with "概率神经网络"

Handwritten character recognition falls within the domain of optical character recognition, employing probabilistic neural networks as classifiers to categorize handwritten digits represented as binary images. The resulting classifier achieves 100% accuracy on training samples, with implementation involving feature extraction and pattern layer optimization.

MATLAB 259 views Tagged

The following code implements a recognition application using neural network technology. The probabilistic neural network model aids in pattern identification by incorporating intelligent learning mechanisms through neural network architectures.

MATLAB 203 views Tagged

PNN, also known as Probabilistic Neural Network, was initially proposed by mathematician Specht in 1990 and subsequently refined by researchers including Master [1995]. This network architecture has been successfully applied across multiple domains including machine learning, artificial intelligence, and automatic control systems. Compared to multi-layer feedforward networks, PNN demonstrates simpler mathematical principles and easier implementation through its probability density function estimation approach using Parzen windows and radial basis functions.

MATLAB 208 views Tagged