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针对混沌通信系统中非线性信道干扰问题,基于混沌信号重构理论和Legendre正交多项式结构,提出了一种自适应神经Legendre正交多项式信道均衡器,并给出相应的归一化最小均方算法.仿真研究表明:所提出的自适应神经Legendre正交多项式信道均衡器能有效地消除线性和非线性信道干扰,均衡器输出信号能反映出混沌信号的特性,具有良好的抗干扰性能.该均衡器的结构简单,权系数参数较少,收敛稳定性较好.
Aiming at the problem of nonlinear channel interference in chaotic communication system, an adaptive neural Legendre orthogonal polynomial channel equalizer is proposed based on chaotic signal reconstruction theory and Legendre orthogonal polynomial structure. Corresponding normalized least squares Algorithm.The simulation results show that the proposed adaptive neural Legendre orthogonal polynomial channel equalizer can effectively eliminate the linear and nonlinear channel interference and the equalizer output signal can reflect the chaotic signal characteristics and has good anti-jamming performance. The structure of the equalizer is simple, the weight coefficient parameters are less, and the convergence stability is better.