A new hybrid descent method with application to the optimal design of finite precision FIR filters

Ka Fai Cedric Yiu, W. Y. Yan, K. L. Teo, S. Y. Low

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

In this paper, the problem of the optimal design of discrete coefficient FIR filters is considered. A novel hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm operates on the space of orthogonal matrices and is used to locate descent points for previously converged local minima. The gradient-based method is derived from converting the discrete problem to a continuous problem via the Stiefel manifold, where convergence can be guaranteed. To demonstrate the effectiveness of the proposed hybrid descent method, several numerical examples show that better discrete filter designs can be sought via this hybrid descent method.
Original languageEnglish
Pages (from-to)725-735
Number of pages11
JournalOptimization Methods and Software
Volume25
Issue number5
DOIs
Publication statusPublished - 1 Oct 2010

Keywords

  • Finite precision
  • FIR filter design
  • Hybrid descent method
  • Simulating annealing

ASJC Scopus subject areas

  • Software
  • Control and Optimization
  • Applied Mathematics

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