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OverviewFull Product DetailsAuthor: João Paulo Coelho (Instituto Politécnico de Bragança, Portugal) , Tatiana M. Pinho (INESC TEC Technology and Science, Porto, Portugal) , José Boaventura-Cunha (Universidade de Trás-os-Montes e Alto Douro, Escola de Ciências e Tecnologia, Vila Real, Portugal)Publisher: Taylor & Francis Ltd Imprint: CRC Press Weight: 0.453kg ISBN: 9780367779344ISBN 10: 036777934 Pages: 282 Publication Date: 31 March 2021 Audience: College/higher education , General/trade , Tertiary & Higher Education , General Format: Paperback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsIntroduction 1. Probability theory and stochastic processes 2. Discrete hidden Markov models 3. Continuous hidden Markov models 4. Autoregressive Markov models 5. Selected Applications Glossary References IndexReviewsA distinguishing feature of this book is that it provides the MATLAB code for the various algorithms covered. This would make it an excellent text for a course in the subject, as it would enable the students to experiment themselves with the algorithms encountered. Another good feature is that each chapter ends with a clear summary. All libraries serving programs in computer science should acquire this volume, and it would be worth considering as a textbook by instructors teaching courses on hidden Markov models. -- R. Bharath, emeritus, Northern Michigan University in CHOICE magazine Author InformationJoão Paulo Coelho is an adjunct professor, and currently the Electrical Engineering course director, at the Polytechnic Institute of Bragança. He is also a researcher at CeDRI and holds a Ph.D. degree in computational intelligence applied to agricultural greenhouses. He has been involved, as a researcher member, in several scientific projects at both the national and European level. His research interests include control systems design, machine learning, electronic instrumentation, embedded systems and discrete-event computer simulation. Tatiana M. Pinho graduated in Energy Engineering from the University of Trás-os-Montes e Alto Douro (UTAD), Portugal in 2011 and received the MSc degree in Energy Engineering from UTAD in 2013. In 2018, she received the Ph.D. degree in Electrical and Computer Engineering in UTAD and INESC TEC Technology and Science, supported by the FCT. Presently she is a postdoctoral researcher at the INESC TEC and her research interests include systems’ modeling and adaptive control. José Boaventura-Cunha graduated in Electronics and Telecommunications Engineering and has a Ph.D. degree in Electrical and Computer Engineering. Presently he is an Associate Professor with habilitation at the UTAD University, a senior researcher at the INESC-TEC and member of IFAC and IEEE. He has coordinated/participated in several national and international research projects aiming the development of new instrumentation, modelling and control technologies applied to agriculture. His research interests include modeling, system identification and adaptive control. Tab Content 6Author Website:Countries AvailableAll regions |
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