A new normalized subband adaptive filter under minimum error entropy criterion. Issue 6 (September 2016)

• Record Type: Journal Article
• Authors: Lu, Lu; Zhao, Haiquan; Chen, Chenxi
• Is Part Of: Signal, image and video processing. Volume 10:Issue 6(2016)
• Page Start: 1097
• Page End: 1103
• Publication Date: 2016-09
• Subjects: Subband adaptive filtering -- Convergence analysis -- Minimum error entropy -- Low signal-to-noise ratio (SNR); Signal processing -- Digital techniques -- Periodicals; Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; 621.3822
• DOI: 10.1007/s11760-016-0864-y
• Languages: English
• ISSNs: 1863-1703

Abstract

Abstract A new normalized subband adaptive filter based on the minimum error entropy criterion (MEE-NSAF) is proposed for identifying a highly noisy system. The MEE-NSAF utilizes a kernel function and a number of past errors in adaptation, whereas the classical NSAF relies only on the current error signal. Moreover, the stability of the MEE-NSAF is analyzed. To further improve the performance of the MEE-NSAF under the sparse impulse responses, an improved proportionate MEE-NSAF (MEE-IPNSAF) algorithm is proposed. Simulation results show that the proposed algorithms can achieve improved performance as compared with the conventional NSAF when noise gets severe.