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. © 2006 IEEE.
| Original language | English |
|---|---|
| Article number | 5492228 |
| Pages (from-to) | 1140-1148 |
| Journal | IEEE Transactions on Neural Networks |
| Volume | 21 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - Jul 2010 |
Research Keywords
- global convergence in finite time
- k-winners-take-all operation
- Lyapunov function
- recurrent neural network
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