Signal denoising and ultrasonic flaw detection via overcomplete and sparse representations

Journal of the Acoustical Society of America

Volumn 124, Issue 5, 2008, Pages 2963-2972

  Zhang, Guang Ming ^a   Harvey, David M ^a   Braden, Derek R ^b  

^a LIVERPOOL JOHN MOORES UNIVERSITY   (United Kingdom)

^b Delphi Electronics and Safety   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BACKGROUND NOISES; CORRELATED NOISES; FLAW ECHOES; GABOR DICTIONARIES; GAUSSIAN ADDITIVE NOISES; NOISE CONTRIBUTIONS; NOISE ENERGIES; NOISE SUPPRESSIONS; OVER COMPLETE; OVERCOMPLETE DICTIONARIES; POST-PROCESSING; PRIORI INFORMATIONS; SIGNAL DENOISING; SIGNAL PROCESSORS; SPARSE BAYESIAN LEARNINGS; SPARSE REPRESENTATIONS; SPARSE SIGNAL REPRESENTATIONS; THRESHOLDING; ULTRASONIC FLAW DETECTIONS; ULTRASONIC SIGNALS;

ACOUSTIC NOISE; CONCRETE BRIDGES; LEARNING ALGORITHMS; LEARNING SYSTEMS; SIGNAL PROCESSING; ULTRASONIC APPLICATIONS; ULTRASONICS; WAVELET TRANSFORMS;

ULTRASONIC TESTING;

ACOUSTICS; ALGORITHM; ARTICLE; BAYES THEOREM; MATERIALS TESTING; NOISE REDUCTION; PRIORITY JOURNAL; SIGNAL NOISE RATIO; SIGNAL PROCESSING; ULTRASOUND;

ALGORITHMS; BAYES THEOREM; MATERIALS TESTING; NERVE NET; NOISE; NORMAL DISTRIBUTION; SIGNAL PROCESSING, COMPUTER-ASSISTED; ULTRASONICS;

EID: 56749177768     PISSN: 00014966     EISSN: None     Source Type: Journal    
DOI: 10.1121/1.2982414     Document Type: Article

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