A Novel Recurrent Neural Network With One Neuron and Finite-Time Convergence for -Winners-Take-All Operation

摘要

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 $k$th 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.