Iterative Reweighted Least-Squares Design of FIR Filters

C. Sidney Burrus, J. A. Barreto, Ivan W. Selesnick

Research output: Contribution to journalArticlepeer-review


This paper develops a new iterative reweighted least squares algorithm for the design of optimal L, approximation FIR filters. The algorithm combines a variable p technique with a Newton’s method to give excellent robust initial convergence and quadratic final convergence. Details of the convergence properties when applied to the Lp optimization problem are given. The primary purpose of Lp approximation for filter design is to allow design with different error criteria in pass and stopband and to design constrained L2 approximation filters. The new method can also be applied to the complex Chebyshev approximation problem and to the design of 2-D FIR filters.

Original languageEnglish (US)
Pages (from-to)2926-2936
Number of pages11
JournalIEEE Transactions on Signal Processing
Issue number11
StatePublished - Nov 1994

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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