摘要： 针对未知记忆深度的Hammerstein模型，提出一种基于高阶累积量的Hammerstein模型记忆效应盲辨识方法。将Hammerstein模型中对记忆深度的确定转换为对模型输出信号高阶累积量扩展矩阵的求秩问题，给出对角元素乘积(NPODE)方法以确定记忆深度，分别比较该方法与GM直接定阶法、拐点法的鲁棒性。结合提出的记忆深度估计算法，给出线性记忆模块系数的提取方法。理论推导与仿真结果表明，线性记忆模块系数的提取过程不受无记忆非线性效应的影响。

关键词: 对角元素乘积方法, Hammerstein模型, 记忆效应, 累积量, 记忆深度

Abstract: Aiming at the Hammerstein model with unknown memory depth, this paper proposes a blind identification method of memory effect for Hammerstein model based on high cumulant. The memory depth determination is converted into finding the rank of extended matrix constructed by cumulants of system output. In order to yield the rank of cumulant matrix. It proposes Nonlinear Product Of Diagonal Entry(NPODE) method, and simulation verifies its robustness by comparing with GM method and inflexion method. Linear block coefficients extraction method is given, the theoretical derivation and simulation result indicates that the extraction process is not affected by the strength of nonlinearity of Hammerstein model.

Key words: Nonlinear Product Of Diagonal Entry(NPODE) method, Hammerstein model, memory effect, cumulant, memory depth

中图分类号: 

• TN911.7