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Hidden Markov models
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231	Non linear statistical models to improve wind power forecasts M. Pilar Muñoz1, Josep A. Sánchez-Espigares1, M. Dolores Márquez2 1 Barcelona-Tech. Universitat Politècnica de Catalunya, Barcelona, Spain 2 Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:20 Non-linear systems Directional statistics Econometrics SETAR Von Mises distribution Hidden Markov model Statistical model Wind power forecasting Time series Statistics Markov models Time series analysis
232	CLASSIFICATION OF WOLF CALL TYPES USING REMOTE SENSOR TECHNOLOGY _______________ A Thesis Add to Reading List Source URL: hpwren.ucsd.edu Language: English - Date: 2007-07-17 00:47:07 Hidden Markov model Geography Earth Planetary science Markov models Cartography Remote sensing
233	Making a Robot Recognize Three Simultaneous Sentences in Real-Time Add to Reading List Source URL: jmvalin.ca Language: English - Date: 2005-10-13 06:24:28 Science Probability and statistics Speech recognition Computer accessibility Mixture model Speech enhancement Mel-frequency cepstrum Hidden Markov model Julius Statistics Computational linguistics Markov models
234	Conditional Random Fields: An Introduction∗ Hanna M. Wallach February 24, 2004 1 Add to Reading List Source URL: www.inference.phy.cam.ac.uk Language: English - Date: 2004-09-21 19:00:07 Probability theory Statistical theory Graphical models Bayesian statistics Machine learning Conditional random field Hidden Markov model Markov random field Information theory Statistics Probability and statistics Probability
235	HERD: The Highest Expected Reward Decoding for HMMs with Application to Recombination Detection ˇ Brejová Brona Department of Computer Science Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2010-08-20 17:45:42 Statistics Viterbi algorithm Probability and statistics Hidden Markov model Forward–backward algorithm Pointwise Mathematics Annotation Markov models Error detection and correction Dynamic programming
236	Microsoft Word - UBM v8.0.doc Add to Reading List Source URL: wiki.inf.ed.ac.uk Language: English - Date: 2009-05-20 07:31:50 Estimation theory Covariance and correlation Markov models Maximum likelihood Statistical theory Hidden Markov model Covariance N-gram Statistics Probability Science
237	Webpage Understanding: an Integrated Approach Jun Zhu ∗ Dept. of Comp. Sci. & Tech. Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2007-06-15 03:38:48 Mathematics Statistics Machine learning Artificial intelligence Probability theory Conditional random field Hidden Markov model Pattern recognition Markov random field Theoretical computer science Graphical models Applied mathematics
238	Hidden Conditional Random Fields for Phone Recognition Yun-Hsuan Sung 1 and Dan Jurafsky 2 1 Electrical Engineering, Stanford University Add to Reading List Source URL: nlp.stanford.edu Language: English - Date: 2010-01-07 17:30:55 Probability and statistics Probability Hidden Markov model Conditional random field Speech recognition Mutual information Sequence labeling Generative model Viterbi algorithm Statistics Machine learning Markov models
239	IEEE J-STSP SPECIAL ISSUE ON STATISTICAL LEARNING METHODS FOR SPEECH AND LANGUAGE PROCESSING 1 Speech Recognition with Flat Direct Models Patrick Nguyen, Member, IEEE, Georg Heigold, and Geoffrey Zweig, Senior Member, I Add to Reading List Source URL: research.microsoft.com Language: English - Date: 2011-02-15 10:28:34 Markov models Abstract algebra Automatic identification and data capture Computer accessibility Speech recognition Hidden Markov model Mutual information Modal logic Exponentiation Mathematics Logic Computational linguistics
240	[Final] Scaled On-line Unsupervised Learning Algorithm Add to Reading List Source URL: www.islab.ntua.gr Language: English - Date: 2012-10-14 18:35:21 Bioinformatics Machine learning Hidden Markov model Self-organizing map Unsupervised learning Computational statistics HMM Layered hidden Markov model Neural networks Statistics Markov models