A novel vector representation of stochastic signals based on adapted ergodic HMMs

IEEE Signal Processing Letters

Volumn 17, Issue 8, 2010, Pages 715-718

  Tang, Hao ^a   Hasegawa Johnson, Mark ^a   Huang, Thomas ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

Distance metric learning; hidden Markov model; pattern recognition; stochastic signal; vector representation

Indexed keywords

CLASSIFICATION ,; DISTANCE METRIC LEARNING; ERGODICS; IMAGE-BASED; LINEAR DISCRIMINANT ANALYSIS; STOCHASTIC SIGNALS; VECTOR REPRESENTATIONS;

DISCRIMINANT ANALYSIS; IMAGE RECOGNITION; OBJECT RECOGNITION; STOCHASTIC MODELS; STOCHASTIC SYSTEMS; VECTORS;

HIDDEN MARKOV MODELS;

EID: 77953988140     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2010.2051945     Document Type: Article

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