A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation

Abstract

In this paper, based on a one-neuron recurrent neural network, a novel k-winners-take-all ( k -WTA) network is proposed. Finite time convergence of the proposed neural network is proved using the Lyapunov method. The k-WTA operation is first converted equivalently into a linear programming problem. Then, a one-neuron recurrent neural network is proposed to get the kth or (k+1)th largest inputs of the k-WTA problem. Furthermore, a k-WTA network is designed based on the proposed neural network to perform the k-WTA operation. Compared with the existing k-WTA networks, the proposed network has simple structure and finite time convergence. In addition, simulation results on numerical examples show the effectiveness and performance of the proposed k-WTA network.

DOI: 10.1109/TNN.2010.2050781

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@article{Liu2010ANR, title={A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation}, author={Qingshan Liu and Chuangyin Dang and Jinde Cao}, journal={IEEE transactions on neural networks}, year={2010}, volume={21 7}, pages={1140-8} }