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基于优化理论和神经网络理论提出了一种优化神经网络最佳多用户检测器，将DS－CDMA通信中的多用户信号检测问题看作一种组合优化问题，利用神经网络能有效地求解优化问题的优势：推导了一种优化神经网络最佳多用户检测器，理论分析和计算结果表明：1）在误比特性能和抗多址干扰性能上这种检测器均优于传统检测器和解相关检测器；2）在抗“远近”干扰能力方面，这种检测器优于传统检测器而弱于解相关检测器；3）易于实时应用和VLSI实现。
Based on optimization theory and neural network theory, an optimal multi-user detector based on neural network optimization is proposed. The multi-user signal detection problem in DS-CDMA communication is considered as a combinatorial optimization problem, which can effectively solve the optimization problem by using neural network Advantages: A best multi-user detector with neural network optimization is derived. The theoretical analysis and calculation results show that: 1) This detector is superior to the traditional detector and decorrelation detector in terms of bit error ratio and anti-multiple access interference performance 2) This detector is superior to conventional detectors and de-correlated detectors in terms of interference immunity; 3) is easy to implement in real time and with VLSI.