LTF-C - Neural Network for Solving Classification Problems

Authors:
Marcin Wojnarski
Affiliations:
-
Venue:
PPAM '01 Proceedings of the th International Conference on Parallel Processing and Applied Mathematics-Revised Papers
Year:
2001

Citing 3
Cited 0

Machine learning, neural and statistical classification

Machine learning, neural and statistical classification
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Handbook of Neural Computation
Neural Networks for Identification, Prediction, and Control

Neural Networks for Identification, Prediction, and Control

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Abstract

This paper presents a new model of an artificial neural network solving classification problems - Local Transfer Function Classifier (LTF-C). Its structure is very similar to this of the Radial Basis Function neural network (RBF), however it utilizes entirely different learning algorithms, including not only changing positions and sizes of neuron reception fields, but also inserting and removing neurons during the training. Applying this network to practical tasks, such as handwritten digit recognition, shows, that it is characterized by high accuracy, small size and high speed of functioning.