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• W3181425324 abstract "A k-winners-take-all (k-WTA) neural network is designed and applied to a task assignment problem in a multi-robot competitive target tracking scenario in this paper. The proposed neural network features a single neuron and a non-hard-limiting activation function, which greatly simplifies the model structure and reduces the computation cost. This neural network has finite-time convergence property and can be applied to real-time situations. The stability and convergence property of the neural network is theoretically analyzed. Simulations of handling a situation that a target moves at a higher speed than tracking robots are conducted to demonstrate the effectiveness of the designed scheme." @default.
• W3181425324 created "2021-07-19" @default.
• W3181425324 creator A5042160852 @default.
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• W3181425324 date "2021-10-01" @default.
• W3181425324 modified "2023-10-14" @default.
• W3181425324 title "Multi-robot competitive tracking based on k-WTA neural network with one single neuron" @default.
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• W3181425324 doi "https://doi.org/10.1016/j.neucom.2021.07.020" @default.
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