Set-Membership Constrained Frequency-Domain Algorithm

Author(s)

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

Affiliation

^[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

• Document type: Journal article
• Source: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS; v. 68, n. 2, p. 797-801, FEB 2021.
• Web of Science Citations: 0

Abstract

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)

• FAPESP's process: 19/06280-1 - Integration, transformation, dataset augmentation and quality control for intermediate representation
• Grantee: Hamed Yazdanpanah
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
• Grantee: Roberto Marcondes Cesar Junior
• Support Opportunities: Research Projects - Thematic Grants