Abstract
As the implementation cost of a digital filter mainly depends on the number of filter coefficients, the filters with sparse coefficients are of great interest. In this paper, a reweighted l 1 minimization procedure is proposed for the design of a class of linear-phase FIR filters with sparse coefficients. The proposed design algorithm is accomplished in two phases. In the first phase, we utilize the reweighted l 1 norm to identify the zero coefficient positions. In the second phase, the sparse non-zero coefficients of the filter are re-optimized either in the mimimax sense or least-square sense. Numerical examples are given to show the effectiveness of the proposed method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
