Joint logarithmic hyperbolic cosine robust sparse adaptive algorithms

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dc.contributor.author Kumar, Krishna
dc.contributor.author Bhattacharjee, Sankha Subhra
dc.contributor.author George, Nithin V.
dc.date.accessioned 2020-07-25T16:20:36Z
dc.date.available 2020-07-25T16:20:36Z
dc.date.issued 2020-07
dc.identifier.citation Kumar, Krishna; Bhattacharjee, Sankha Subhra and George, Nithin V., "Joint logarithmic hyperbolic cosine robust sparse adaptive algorithms", IEEE Transactions on Circuits and Systems II: Express Briefs, DOI: 10.1109/TCSII.2020.3007798, Jul. 2020. en_US
dc.identifier.issn 1549-7747
dc.identifier.issn 1558-3791
dc.identifier.uri http://dx.doi.org/10.1109/TCSII.2020.3007798
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/5568
dc.description.abstract Recently, the logarithmic hyperbolic cosine adaptive filter (LHCAF) was proposed and was seen to demonstrate excellent robustness against impulsive interference. However, for the modelling of sparse systems, it may not provide optimal performance as it does not take into account the sparse nature of the system. To improve the modelling accuracy and convergence performance, a sparsity aware zero attraction LHCAF (ZA-LHCAF) and a reweighted zero attraction LHCAF (RZA-LHCAF) is proposed. To further improve the performance for modelling of sparse systems in impulsive environments, a joint logarithmic hyperbolic cosine function (JLHCF) is proposed as the cost function. The corresponding update rule, called the joint logarithmic hyperbolic cosine adaptive filter (JLHCAF) is deduced and the bound on learning rate is derived. A room equalization scenario is also considered and an improved sparsity aware robust algorithm based on JLHCF, namely the filtered-x JLHCAF (Fx-JLHCAF) is proposed for the same. Extensive simulation studies carried out for different system identification scenarios, under Gaussian and non-Gaussian disturbances and a room equalization scenario, demonstrate the superior performance achieved by JLHCAF over existing sparsity aware robust adaptive filters.
dc.description.statementofresponsibility by Krishna Kumar, Sankha Subhra Bhattacharjee and Nithin V. George
dc.language.iso en_US en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.subject Robust adaptive filter en_US
dc.subject system identification en_US
dc.subject room equalization en_US
dc.subject correntropy en_US
dc.subject hyperbolic function. en_US
dc.title Joint logarithmic hyperbolic cosine robust sparse adaptive algorithms en_US
dc.type Article en_US
dc.relation.journal IEEE Transactions on Circuits and Systems II: Express Briefs


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