A matrix-based IRLS algorithm for the least \(l_p\)-norm design of 2-D FIR filters

DOI10.1007/s11045-017-0543-3zbMath1429.94039OpenAlexW2772956709MaRDI QIDQ1710933

Zhiping Lin, Xiaoping Lai, Ruijie Zhao, Xiaoying Hong

Publication date: 24 January 2019

Published in: Multidimensional Systems and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11045-017-0543-3

zbMATH Keywords

2-D FIR filteriterative reweighted least squares algorithmleast \(l_p\)-norm designmatrix-based algorithm

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (1)

A reweighted symmetric smoothed function approximating \(L_0\)-norm regularized sparse reconstruction method

Uses Software

• SDPA

Cites Work

• Unnamed Item
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• Two-dimensional digital filters with sparse coefficients
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• Peak constrained two-dimensional quadrantally symmetric eigenfilter design without transition band specification
• A fast design algorithm for elliptic-error and phase-error constrained LS 2-D FIR filters
• Efficient 2-D based algorithms for WLS designs of 2-D FIR filters with arbitrary weighting functions
• Construction of nearest points in the \(L^ p\), p even, and \(L^ \infty\) norms. I
• Matrix-Based Algorithms for Constrained Least-Squares and Minimax Designs of 2-D Linear-Phase FIR Filters
• A unified approach for the design of 2-D digital filters via semidefinite programming
• The Lawson Algorithm and Extensions
• Convex \(L^ p\) approximation
• Convex \(L^ p\) approximation

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