Sparse FIR Filter Design Using Iterative Reweighted 1-Norm Minimization and Binary Search

被引:0
|
作者
Liu Lei [1 ]
Lai Xiaoping [1 ]
机构
[1] Hangzhou Dianzi Univ, Key Lab IOT & Informat Fus Technol Zhejiang, Hangzhou 310018, Zhejiang, Peoples R China
关键词
FIR filter; sparse filter; iterative reweighted 1-norm minimization; binary search; DIGITAL-FILTERS; LINEAR-PHASE;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Finite impulse response (FIR) filters with sparse coefficients have found many applications because of their low implementation complexity. This paper focuses on the design of sparse FIR filters satisfying prescribed frequency response specifications, which can be described as minimizing the 0-norm of its coefficient vector subject to magnitude constraints on its frequency response. This is an NP-hard problem whose optimal solution is very difficult to find. This paper presents a practical approach to this problem. It uses the iterative reweighted 1-norm minimization method to design a filter with many zero and/or small coefficients and then applies a binary search to finally determine how many and which of those smallest ones can be set to zero while not violating the magnitude constraints on the frequency response. Simulation examples demonstrate the effectiveness of the presented method.
引用
收藏
页码:4846 / 4850
页数:5
相关论文
共 50 条
  • [1] Sparse FIR Filter Design via Partial 1-Norm Optimization
    Jiang, Aimin
    Kwan, Hon Keung
    Tang, Yibin
    Zhu, Yanping
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2020, 67 (08) : 1482 - 1486
  • [2] Design of Sparse FIR Filters Based on Reweighted l1-Norm Minimization
    Yang, Yuhua
    Zhu, Wei-Ping
    Wu, Dalei
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2015, : 858 - 862
  • [3] Iterative reweighted l1 design of sparse FIR filters
    Rusu, Cristian
    Dumitrescu, Bogdan
    [J]. SIGNAL PROCESSING, 2012, 92 (04) : 905 - 911
  • [4] Sparse separable 2-D FIR filter design based on iterative reweighted l1 norm and greedy searching techniques
    Wang, Hao
    Li, Weiqi
    Zhao, Zhijin
    Sun, Jian
    [J]. IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2020, 15 (02) : 218 - 224
  • [5] Sparse FIR Filter Design using Iterative MOCSA
    Kwan, Hon Keung
    Liang, Jiajun
    Jiang, Aimin
    [J]. 2018 IEEE 61ST INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS), 2018, : 952 - 955
  • [6] FIR Filter With Variable Fractional Delay and Phase Shift: Efficient Realization and Design Using Reweighted l1-Norm Minimization
    Johansson, Hakan
    Eghbali, Amir
    [J]. 2013 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2013, : 81 - 84
  • [7] ENHANCING SPARSITY IN LINEAR PREDICTION OF SPEECH BY ITERATIVELY REWEIGHTED 1-NORM MINIMIZATION
    Giacobello, Daniele
    Christensen, Mads Graesboll
    Murthi, Manohar N.
    Jensen, Soren Holdt
    Moonen, Marc
    [J]. 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2010, : 4650 - 4653
  • [8] Sparse Signal Recovery With Minimization of 1-Norm Minus 2-Norm
    Wen, Jinming
    Weng, Jian
    Tong, Chao
    Ren, Chao
    Zhou, Zhengchun
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2019, 68 (07) : 6847 - 6854
  • [9] Sparse Linear Phase FIR Filter Design using Iterative CSA
    Kwan, Hon Keung
    Liang, Jiajun
    Jiang, Aimin
    [J]. 2018 IEEE 23RD INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2018,
  • [10] Sparse FIR Filter Design Using Binary Particle Swarm Optimization
    Wu, Chen
    Zhang, Yifeng
    Shi, Yuhui
    Zhao, Li
    Xin, Minghai
    [J]. IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2014, E97A (12): : 2653 - 2657