Sparse LMS with segment zero attractors for adaptive estimation of sparse signals

• Published in: APCCAS 2010-2010 IEEE Asia Pacific Conference on Circuits and Systems pp. 422 - 425
• Main Authors: Jie Yang, Sobelman, G E
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2010
• Subjects: Adaptive filters; compressive sensing; Convergence; Filtering algorithms; l 1 norm; Least Mean Square (LMS); Least squares approximation; Signal processing algorithms; sparse signals; Speech processing; Steady-state; system identification
• ISBN: 142447454X; 9781424474547
• DOI: 10.1109/APCCAS.2010.5774742

Adaptive sparse signal estimation is needed for obtaining accurate channel knowledge in communication systems where the system response can be assumed to contain many near-zero coefficients. For sparse filter design, the zero-attracting LMS (ZA-LMS) incorporates the l 1 norm penalty function into th...