【摘要】 把人工免疫系统和神经网络系统的信息处理机制引入到进化规划算法(EP),提出了免疫进化规划算法.所提IEP通过使用随机Hopfield神经网络制备疫苗构成新的免疫算子,把新的免疫算子结合到进化规划中,不仅加快了进化规划的收敛速度,并提高了进化规划的全局收敛能力.然后在CDMA系统利用此算法设计了新的多用户检测器.仿真结果证明了该方法能够快速收敛到全局最优解,并且无论抗多址干扰和抗远近效应能力都优于传统方法和一些应用优化算法的多用户检测器.更多还原

【Abstract】 By introducing the information processing mechanism of artificial immune systems and neural network system into evolutionary programming (EP) algorithm, an immune evolutionary programming(IEP)is proposed. IEP constructs new immune operator by preparing vaccines with stochastic Hopfield neural network. The proposed IEP is a hybridization of the EP with new immune operator, and it reduces the computational complexity by providing faster convergence and improving the performance of EP. Then a novel multi-user detector based on IEP is designed for code division multiple access communication systems. Simulation results show that the proposed detector not only converges to global optimal solution quickly, but is also superior to conventional multi-user detector in the capabilities of resistance to multiple access interference and near-far effect.更多还原