Classification of nonstationary narrowband signals using segmented chirp features and hidden Gauss-Markov models

IEEE Transactions on Signal Processing

Volumn 53, Issue 1, 2005, Pages 147-157

  Ainsleigh, Phillip L ^a   Greineder, Stephen G ^a   Kehtarnavaz, Nasser ^b  

^a NAVAL UNDERSEA WARFARE CENTER   (United States)

^b UNIVERSITY OF TEXAS AT DALLAS   (United States)

Author keywords

Covariance scaling; EM algorithm; Fractional Fourier transform; Hidden Markov model; Linear chirp; Linear Gaussian model; Newton algorithm; Piecewise linear FM; Signal classification; SNR weighting

Indexed keywords

ALGORITHMS; BANDWIDTH; COMPUTER SIMULATION; FOURIER TRANSFORMS; MARKOV PROCESSES; MATHEMATICAL MODELS; MATRIX ALGEBRA; NATURAL FREQUENCIES; PIECEWISE LINEAR TECHNIQUES; PROBABILITY DENSITY FUNCTION; SIGNAL TO NOISE RATIO;

COVARIANCE SCALING; FRACTIONAL FOURIER TRANSFORM; HIDDEN MARKOV MODEL; LINEAR CHIRP; LINEAR GAUSSIAN MODEL; NEWTON ALGORITHM; SIGNAL CLASSIFICATION;

SIGNAL DETECTION;

EID: 11844296712     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2004.838945     Document Type: Article

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