Title :
Inhibition and the output map of MVQ neural networks
Author :
Abouali, A.H. ; Porter, W.A.
Author_Institution :
Egyptian Res. Center, Cairo, Egypt
Abstract :
We complete the design process of the multiple class vector quantization (MVQ) neural network. The focus of this study is the design of the output layer. The output layer is a group of significant neurons sets. Each set has its own mapping function to the output. The inhibition function enables a single mapping to the output. We also present the canonical architecture of the MVQ network that allows a mix of neurons and the use of higher order moments
Keywords :
learning (artificial intelligence); multilayer perceptrons; neural net architecture; MVQ neural networks; canonical architecture; higher order moments; inhibition function; mapping function; multiple class vector quantization neural network; output map; Books; Communication channels; Displays; Neural networks; Neurons; Testing;
Conference_Titel :
System Theory, 1998. Proceedings of the Thirtieth Southeastern Symposium on
Conference_Location :
Morgantown, WV
Print_ISBN :
0-7803-4547-9
DOI :
10.1109/SSST.1998.660104
