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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. * Provides a unified definition, in-depth treatment, and foundational approach of the HSMMs* Discusses the latest developments and emerging topics in the field of HSMMs* Includes a description of applications in various areas, including Human Activity Recognition, Handwriting Recognition, Network Traffic Characterization and Anomaly Detection, and Functional MRI Brain Mapping* Shows how to master the basic techniques needed for using HSMMs and how to apply them
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