A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation.
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.
Liu
Qingshan
Q
School of Automation, Southeast University, Nanjing 210096, China. qsliu@seu.edu.cn
Dang
Chuangyin
C
Cao
Jinde
J
D000465:Algorithms; D000818:Animals; D005246:Feedback; D005716:Game Theory; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D013997:Time Factors