Journal
NEURAL NETWORKS
Volume 21, Issue 2-3, Pages 406-413Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neunet.2007.12.044
Keywords
recurrent neural network; discontinuous activation function; linear programming; quadratic programming; global convergence; differential inclusion; lyapunov stability
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This paper presents two k-winners-take-all (k-WTA) networks with discontinuous activation functions. The k-WTA operation is first converted equivalently into linear and quadratic programming problems. Then two k-winners-take-all networks are designed based on the linear and quadratic programming formulations. The networks are theoretically guaranteed to be capable of performing the k-WTA operation in real time. Simulation results show the effectiveness and performance of the networks. (C) 2007 Elsevier Ltd. All rights reserved.
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