Analysis and design of unified architectures for zero-attraction-based sparse adaptive filters

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dc.contributor.author Ray, Dwaipayan
dc.contributor.author George, Nithin V.
dc.contributor.author Meher, Pramod Kumar
dc.date.accessioned 2020-02-22T06:10:45Z
dc.date.available 2020-02-22T06:10:45Z
dc.date.issued 2020-01
dc.identifier.citation Ray, Dwaipayan; George, Nithin V. and Meher, Pramod Kumar, “Analysis and design of unified architectures for zero-attraction-based sparse adaptive filters”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, DOI: 10.1109/TVLSI.2020.2965018, vol. 28, no. 5, pp. 1321-1325, Jan. 2020. en_US
dc.identifier.issn 1063-8210
dc.identifier.uri http://dx.doi.org/10.1109/TVLSI.2020.2965018
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/5114
dc.description.abstract Zero-attraction-based adaptive filters are widely used for sparse system identification, where a suitable penalty function is integrated with the least mean square (LMS) framework to improve the convergence behavior of the identification process. In this brief, we have made an attempt to implement some of the most popular zero-attracting algorithms in hardware. The complexity of realization associated with these algorithms is investigated in detail. Following the above analysis, several architectural simplifications are proposed for the reduced-complexity implementation of their penalty functions. We then use these realizations to develop a set of novel design strategies for the efficient implementation of these algorithms. Simulation results show that the performance loss for the proposed algorithms is minimal compared to their standard versions. A detailed synthesis study is also carried out to validate the proposed structures, which demonstrates that the hardware overhead in the proposed designs is marginal compared to the existing delayed LMS architecture.
dc.description.statementofresponsibility by Dwaipayan Ray, Nithin V. George and Pramod Kumar Meher
dc.language.iso en_US en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.subject Sparse adaptive filters en_US
dc.subject sparse system identification en_US
dc.subject unified architectures and low-power designs en_US
dc.subject zero-attracting algorithms en_US
dc.title Analysis and design of unified architectures for zero-attraction-based sparse adaptive filters en_US
dc.type Article en_US
dc.relation.journal IEEE Transactions on Very Large Scale Integration (VLSI) Systems


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