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Informationen zum Autor Shun-Zheng Yu is a professor at the School of Information Science and Technology at Sun Yat-Sen University, China.. He was a visiting scholar at Princeton University and IBM Thomas J. Watson Research Center from 1999 to 2002. He has authored two hundred journal papers that used artificial intelligence/machine learning methods for inference and estimation, among which fifty papers involved hidden semi-Markov models. Professor Yu is a well-recognized expert in the field of HSMMs and their applications. He has developed new estimation algorithms for HSMMs and applied them in various fields. The papers entitled "Hidden Semi-Markov Models (2010)" Published in the Elsevier Journal Artificial Intelligence , "Practical Implementation of an Efficient Forward-Backward Algorithm for an Explicit Duration Hidden Markov Model (2006) published in IEEE Signal Processing Letters", "A Hidden Semi-Markov Model with Missing Data and Multiple Observation Sequences for Mobility Tracking (2003)" Published in the Elsevier Journal Signal Processing and " An Efficient Forward-Backward Algorithm for an Explicit Duration Hidden Markov Model (2003) published in IEEE Signal Processing Letters " have been cited by hundreds of papers. Klappentext Hidden Semi-Markov Models: Theory! Algorithms and Applications provides a unified and foundational approach on Hidden Semi-Markov Models! including various HSMMs (such as the explicit duration! variable transition! and residential time of HSMMs)! inference and estimation algorithms! implementation methods and application instances. . In addition! new developments and state-of-the-art emerging topics as they relate to HSMMs are presented with general examples drawn medicine! engineering and computer science.
List of contents
1. Introduction2. Inference of General Hidden Semi-Markov Model3. Estimation of General Hidden Semi-Markov Model4. Implementation of the Algorithms5. Conventional Models6. Various Duration Distributions8. Variants of HSMM9. Applications of HSMM
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"This book is intended to present theory, models, methods, and applications regarding hidden semi-Markov models...It also provides the latest development and emerging topics concerning this field." --Zentralblatt MATH
