On the K-winners-take-all-network
Advances in neural information processing systems 1
On a magnitude preserving iterative MAXnet algorithm
Neural Computation
1994 Special Issue: Winner-take-all networks for physiological models of competitive learning
Neural Networks - Special issue: models of neurodynamics and behavior
The handbook of brain theory and neural networks
The handbook of brain theory and neural networks
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Neural Networks for Optimization and Signal Processing
Neural Networks for Optimization and Signal Processing
Acoustic recognition of a limited vocabulary in continuous speech
Acoustic recognition of a limited vocabulary in continuous speech
Another K-winners-take-all analog neural network
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Performance analysis for a K-winners-take-all analog neural network: basic theory
IEEE Transactions on Neural Networks
K-winners-take-all circuit with O(N) complexity
IEEE Transactions on Neural Networks
A neural-network contention controller for packet switching networks
IEEE Transactions on Neural Networks
A discrete-time dynamic K-winners-take-all neural circuit
Neurocomputing
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A new analog inhibitory method based winner-take-all (WTA) circuit is proposed. The circuit structure is a binary tree arrangement of two-dimensional neural networks and logic nodes. The connection matrix belongs to the class of diagonally stable matrices and the activation functions are piecewise linear or sigmoidal. The mathematical justification of the strong WTA network functioning, on the basis of the uniqueness and global asymptotic stability of the equilibrium, is given. Simulation examples and the corresponding results are also provided.