根据负梯度搜索原理,推导了滑动平均噪声干扰单输入多输出系统的递阶增广随机梯度算法。为了改进提出算法的收敛速度,在算法中引入遗忘因子,得到递阶增广遗忘梯度算法。数字仿真结果表明所提出的算法估计系统参数是有效的。
According to the negative gradient search principle, a hierarchical extended stochastic gradient (HESG) algorithm is derived for single-input multioutput systems with the moving average noise. In order to improve the convergence rate, a HESG algorithm with a forgetting factor is obtained by introducing a forgetting factor in the HESG algorithm. The simulation results show that the proposed algorithms work quite well.