关键词: 迭代型最小均方噪声抑制算法, 代价函数, 遗忘因子, Kalman增益, 自回归模型

Abstract:

In order to reduce the complexity of the recursive lease M-estimate (RLM) algorithm, The impulse noise suppression function ??(•) is modified. The analysis proves that the modified algorithm still meets the linear equation. In addition, the method of estimating the key threshold ? and ? in function ??(•) is provided, and the modified RLM algorithm to estimating the impulse response vector in the time-varying fading channel is applied. The simulation results show that the modified RLM algorithm is more robust against consecutive impulse noise and have better convergence ability than conventional recursive lease square (RLS).

Key words: recursive lease m-estimate algorithm, cost function, forgetting factor, Kalman gain, auto-regressive model