Efficient Pattern Discrimination with Inhibitory WTA Nets

Authors:
Brijnesh J. Jain;Fritz Wysotzki
Affiliations:
-;-
Venue:
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
Year:
2001

Citing 5
Cited 1

Complex dynamics in winner-take-all neural nets with slow inhibition

Neural Networks
Dynamics of a winner-take-all neural network

Neural Networks
On the piecewise analysis of networks of linear threshold neurons

Neural Networks
A Competitive-Layer Model for Feature Binding and Sensory Segmentation

Neural Computation
On the Computational Power of Winner-Take-All

Neural Computation

Improving the performance of CGPANN for breast cancer diagnosis using crossover and radial basis functions

EvoBIO'13 Proceedings of the 11th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

A mathematical analysis of a special class of winner-takeall networks is given. Starting with a solution in closedform describing the dynamics of the network, we show that an inhibitory winner-take-all net efficiently discriminates input patterns with respect to a canonical measure. This result in combination with further properties suggests an upgrading of the system by incorporating fault tolerance and efficiently generatedevid ential response into the system.