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- W2362577289 abstract "It's more effective to use continuous Hopfield neural network to blindly detect wireless communication signal,but its anti-jamming performance is poor and the algorithm bit error rate is a little high in complex environments,such as in low SNR environment.To conquer the above shortcoming,a new kind of activation function is put forward in this thesis,which can effectively reduce the algorithm sensitivity to noise and greatly improve its anti-jamming capability.Simulation results demonstrate that the improved algorithm has better anti-jamming capability and robustness in complex environments,like low SNR or massive date environment.The improved algorithm shows strong anti-interference ability and robustness,performance has been improved significantly." @default.
- W2362577289 created "2016-06-24" @default.
- W2362577289 creator A5019602223 @default.
- W2362577289 date "2012-01-01" @default.
- W2362577289 modified "2023-09-24" @default.
- W2362577289 title "Blind Detection Algorithm of Hopfield Neural Network With Improved Activation Function" @default.
- W2362577289 hasPublicationYear "2012" @default.
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