Abstract
Proportionate-type adaptive algorithms are commonly used for the identification of sparse impulse responses, like in network and acoustic echo cancellation. In this paper, we propose an optimized proportionate LMS adaptive filter in the context of a state variable model. The algorithm follows an optimization criterion based on the minimization of the system misalignment and uses an iterative procedure for computing the proportionate factors. Consequently, it achieves a proper compromise between the performance criteria, i.e., fast convergence/tracking and low mis adjustment. Simulations performed in the context of sparse system identification indicate the good behavior of the proposed algorithm.
Recommended Citation
S. Ciochina et al., "An Optimized Proportionate Adaptive Algorithm for Sparse System Identification," Conference Record - Asilomar Conference on Signals, Systems and Computers, pp. 1546 - 1550, article no. 7421405, Institute of Electrical and Electronics Engineers, Feb 2016.
The definitive version is available at https://doi.org/10.1109/ACSSC.2015.7421405
Department(s)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
978-146738576-3
International Standard Serial Number (ISSN)
1058-6393
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
26 Feb 2016
