Convergence and Steady-State Properties of the Affine Projection Mixed-Norm Algorithms

被引：0
|
作者：
Ling Liqian [1 ]
Lin Bin [1 ]
Wang Fei [1 ]
Luo Lingling [1 ]
机构：
[1] Dalian Maritime Univ, Coll Informat Sci & Technol, Dalian 116026, Peoples R China
来源：
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS | 2016年 / 386卷
关键词：
Adaptive filter; Steady-state analysis; Mean-square error; Convergence rate;
D O I：
10.1007/978-3-662-49831-6_99
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The affine projection algorithm (APA) attracts a wide attention for its advantages such as simple frame, fast convergence rate, and so on. This paper is based on the AP algorithm to introduce nonlinear update equation for the weight error vector. So the affine projection mixed-norm (APMN) algorithm is proposed. In this paper, we use a new approach to analyse the APMN algorithm. In this thesis, the stability and convergence rate of APMN algorithm are analyzed in theory and, simulation and verification of theoretical analysis is also performed.
引用
收藏
页码：953 / 961
页数：9
相关论文
共 50 条
  • [31] Steady-state performance of hyperslab projection algorithm
    Takahashi, Noriyuki
    Yamada, Isao
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 3829 - 3832
  • [32] A monotone time relaxation matrix procedure for improved convergence to steady-state for CFD algorithms
    Roy, S
    Baker, AJ
    COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 1998, 160 (3-4) : 359 - 382
  • [33] Convergence and steady-state analysis of the cost function adaptation algorithms for data echo cancellation
    Rusu, C
    Cowan, CFN
    ISCAS 2000: IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS - PROCEEDINGS, VOL IV: EMERGING TECHNOLOGIES FOR THE 21ST CENTURY, 2000, : 357 - 360
  • [34] TRACKING PROPERTIES AND STEADY-STATE PERFORMANCE OF RLS ADAPTIVE FILTER ALGORITHMS
    ELEFTHERIOU, E
    FALCONER, DD
    IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING, 1986, 34 (05): : 1097 - 1110
  • [35] Convergence analysis of the variable weight mixed-norm LMS-LMF adaptive algorithm
    Zerguine, A
    Aboulnasr, T
    CONFERENCE RECORD OF THE THIRTY-FOURTH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, 2000, : 279 - 282
  • [36] Convergence acceleration for the steady-state Euler equations
    Brandén, H
    Holmgren, S
    COMPUTERS & FLUIDS, 2003, 32 (08) : 1075 - 1092
  • [37] A comparative analysis of the convergence regions for different parallel affine projection algorithms
    Artinescu, Irina Maria
    STUDIA UNIVERSITATIS BABES-BOLYAI MATHEMATICA, 2018, 63 (03): : 401 - 411
  • [38] Genetic algorithms aid steady-state modeling
    Rakestraw, Roy
    Pipe Line Industry, 1991, 74 (05):
  • [39] Reinforcement learning in steady-state genetic algorithms
    Lee, CY
    Antonsson, EK
    CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2002, : 1793 - 1797
  • [40] Convergence properties of affine projection and normalized data reusing methods
    Soni, RA
    Gallivan, KA
    Jenkins, WK
    CONFERENCE RECORD OF THE THIRTY-SECOND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1 AND 2, 1998, : 1166 - 1170
12345