Blind Detection Algorithm of Hopfield Neural Network With Improved Activation Function

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.