A fast algorithm for AR parameter estimation using a novel noise-constrained least-squares method

Neural Networks

Volumn 23, Issue 3, 2010, Pages 396-405

  Xia, Youshen ^a   Kamel, Mohamed S ^b   Leung, Henry ^c  

^a FUZHOU UNIVERSITY   (China)

^b UNIVERSITY OF WATERLOO   (Canada)

^c UNIVERSITY OF CALGARY   (Canada)

Author keywords

Autoregressive parameter estimation; Fast learning algorithm; Fixed step length; Mean square error; Noise constrained least squares method; Robust estimate

Indexed keywords

AUTO-REGRESSIVE; AUTOREGRESSIVE PARAMETER ESTIMATION; FAST LEARNING; LEAST SQUARES METHODS; ROBUST ESTIMATE; STEP LENGTH;

CONVERGENCE OF NUMERICAL METHODS; GAUSSIAN NOISE (ELECTRONIC); METAL ANALYSIS; PARAMETER ESTIMATION;

LEARNING ALGORITHMS;

ARTICLE; COMPUTER SIMULATION; CONTROLLED STUDY; INFORMATION PROCESSING; LEARNING ALGORITHM; LINEAR SYSTEM; MATHEMATICAL COMPUTING; PARAMETER; PREDICTION; PRIORITY JOURNAL; REGRESSION ANALYSIS; WHITE NOISE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; LEAST-SQUARES ANALYSIS; NORMAL DISTRIBUTION; TIME FACTORS;

EID: 76849091485     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2009.11.004     Document Type: Article

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