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NIPS
2004
15 years 7 months ago
A Hidden Markov Model for de Novo Peptide Sequencing
De novo Sequencing of peptides is a challenging task in proteome research. While there exist reliable DNA-sequencing methods, the highthroughput de novo sequencing of proteins by ...
Bernd Fischer, Volker Roth, Joachim M. Buhmann, Jo...
ISMB
1993
15 years 7 months ago
Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein familyor the columns of a multiple alignment of that famil...
Michael Brown, Richard Hughey, Anders Krogh, I. Sa...
NAACL
1994
15 years 7 months ago
On-Line Cursive Handwriting Recognition Using Hidden Markov Models and Statistical Grammars
The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuou...
John Makhoul, Thad Starner, Richard M. Schwartz, G...
EMNLP
2010
15 years 4 months ago
Crouching Dirichlet, Hidden Markov Model: Unsupervised POS Tagging with Context Local Tag Generation
We define the crouching Dirichlet, hidden Markov model (CDHMM), an HMM for partof-speech tagging which draws state prior distributions for each local document context. This simple...
Taesun Moon, Katrin Erk, Jason Baldridge
ICASSP
2011
IEEE
14 years 10 months ago
Joint modeling of observed inter-arrival times and waveform data with multiple hidden states for neural spike-sorting
We present a novel, maximum likelihood framework for automatic spike-sorting based on a joint statistical model of action potential waveform shape and inter-spike interval duratio...
Brett Matthews, Mark Clements