Smoothed least mean p-power error criterion for adaptive filtering

1. Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University, Xi'an, 710049, China 2. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China 3. School of Automation & Information Engineering, Xi'an University of Technology, Xi'an 710048, China 4. Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611 USA Fax: 86-29-82668672,Tel:86-29-82668802 ext. 8009, [email protected] Abstract— In this paper, we propose a novel error criterion for adaptive filtering, namely the smoothed least mean p -power (SLMP) error criterion, which aims to minimize the mean p -power