Optimal Hopfield Neural Network and Applicationg for Multi-User Detection

摘要

Hopfield neural network without learning rules, not need training, and not self-learning, to adjust weight by the design process of Lyapunov function, generalized penalty function is combined with the energy function of Hopfield neural network, , a more suitable structure of the new objective function is built based on the minimal average output energy norm, An improved Hopfield neural network method of achieving DS/CDMA blind multi-user detection is discussed. Simulation results show that that the algorithm significantly improved in bit error rate and anti- near-far effect.