Hidden Markov models with nonelliptically contoured state densities

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 12, 2010, Pages 2297-2304

  Chatzis, Sotirios P ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

expectation maximization; Hidden Markov models; multivariate normal inverse Gaussian (MNIG) distribution; sequential data modeling

Indexed keywords

COMMUNICATION SIGNALS; COMPUTATIONALLY EFFICIENT; CONTINUOUS ATTRIBUTE; ELLIPTICALLY CONTOURED DISTRIBUTIONS; EMISSION DENSITY; EXPECTATION MAXIMIZATION; FINITE MIXTURES; GAUSSIANS; HEAVY-TAILED; HIDDEN STATE; MIXTURE COMPONENTS; MODEL EFFICIENCY; MULTIVARIATE NORMAL INVERSE GAUSSIAN DISTRIBUTIONS; OVERFITTING; SEQUENTIAL DATA; STATE DENSITIES; T-DENSITY; TRAINING DATA SETS;

GAUSSIAN DISTRIBUTION; IMAGE SEGMENTATION; MAXIMUM PRINCIPLE; NORMAL DISTRIBUTION; OPTIMIZATION; SIGNAL PROCESSING;

HIDDEN MARKOV MODELS;

EID: 78049528820     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2010.153     Document Type: Article

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