A general solution to blind inverse problems for sparse input signals

Neurocomputing

Volumn 69, Issue 1-3, 2005, Pages 198-215

  Luengo, David ^a   Santamaría, Ignacio ^b   Vielva, Luis ^b  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^b UNIVERSITY OF CANTABRIA   (Spain)

Author keywords

Blind channel identification; Blind deconvolution; Blind equalization; Blind source separation; SIMO and MIMO systems; Sparse input signals

Indexed keywords

COMPUTER SIMULATION; INVERSE PROBLEMS; MATHEMATICAL MODELS; MONTE CARLO METHODS; STATISTICAL METHODS; WHITE NOISE;

BLIND CHANNEL IDENTIFICATION; BLIND DECONVOLUTION; BLIND EQUALIZATION; SPARSE INPUT SIGNALS;

BLIND SOURCE SEPARATION;

ALGORITHM; AMPLITUDE MODULATION; ARTICLE; CANONICAL ANALYSIS; CLUSTER ANALYSIS; COMPUTER ANALYSIS; CONTROLLED STUDY; LINEAR SYSTEM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; METHODOLOGY; MONTE CARLO METHOD; PRIORITY JOURNAL; PROBLEM SOLVING; SEQUENTIAL ANALYSIS; SIGNAL PROCESSING;

EID: 27844555482     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.02.019     Document Type: Article

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