To address the estimation bias caused by ignoring input noise in existing adaptive filtering algorithms, a new proportionate-type algorithm is proposed in this paper. First, a bias-compensation term is derived based o...
详细信息
To address the estimation bias caused by ignoring input noise in existing adaptive filtering algorithms, a new proportionate-type algorithm is proposed in this paper. First, a bias-compensation term is derived based on an unbiased criterion when constructing the cost function of the algorithm to achieve unbiased estimation. Next, this bias-compensation term is integrated into the mu-law Pnlms (MPnlms) algorithm to design the bias-compensated Pnlms combined with the multi-segment function (BC-MS-Pnlms) algorithm. Simulation results for echo paths and underwater channels demonstrate that the BC-MS-Pnlmsalgorithm outperforms other sparse-type algorithms in sparse experimental environments.
暂无评论