Self Organizing Neural Networks for the Identification Problem

Part of Advances in Neural Information Processing Systems 1 (NIPS 1988)

Authors

Manoel Tenorio, Wei-Tsih Lee

Abstract

This work introduces a new method called Self Organizing Neural Network (SONN) algorithm and demonstrates its use in a system identification task. The algorithm constructs the network, chooses the neuron functions, and adjusts the weights. It is compared to the Back-Propagation algorithm in the identification of the chaotic time series. The results shows that SONN constructs a simpler, more accurate model. requiring less training data and epochs. The algorithm can be applied and generalized to appilications as a classifier.