Set-Membership Constrained Frequency-Domain Algorithm

Autor(es)

Lim, Markus V. S. ^[1] ; Diniz, Paulo S. R. ^[1] ; Yazdanpanah, Hamed ^[2]

Afiliação do(s) autor(es)

^[1] Univ Fed Rio de Janeiro, Poli & PEE COPPE, BR-21941909 Rio De Janeiro - Brazil

^[2] Univ Sao Paulo, Dept Comp Sci, BR-05508090 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS; v. 68, n. 2, p. 797-801, FEB 2021.
• Citações Web of Science: 0

Resumo

In this brief, we propose a new frequency-domain adaptive filtering algorithm within the set-membership filtering (SMF) paradigm. Algorithms employing the previously proposed frequency-domain SMF (FD-SMF) concept are not capable of performing linear convolutions (i.e., linear filtering operations), but only circular convolutions. Here, we overcome such limitation by generalizing the FD-SMF concept to allow for linear convolutions, and we propose a new algorithm following this extended FD-SMF concept. Synthetic and real-life simulation results confirm that the proposed algorithm can perform quite better than its non-SMF counterpart, achieving faster convergence and requiring much fewer computations. (AU)

• Processo FAPESP: 19/06280-1 - Integração, transformação, aumento de dados e controle de qualidade para representações intermediárias
• Beneficiário: Hamed Yazdanpanah
• Modalidade de apoio: Bolsas no Brasil - Pós-Doutorado
• Processo FAPESP: 15/22308-2 - Representações intermediárias em Ciência Computacional para descoberta de conhecimento
• Beneficiário: Roberto Marcondes Cesar Junior
• Modalidade de apoio: Auxílio à Pesquisa - Temático