Hidden Markov Models and Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hidden Markov Models and Applications write by Nizar Bouguila. This book was released on 2022-05-19. Hidden Markov Models and Applications available in PDF, EPUB and Kindle. This book focuses on recent advances, approaches, theories, and applications related Hidden Markov Models (HMMs). In particular, the book presents recent inference frameworks and applications that consider HMMs. The authors discuss challenging problems that exist when considering HMMs for a specific task or application, such as estimation or selection, etc. The goal of this volume is to summarize the recent advances and modern approaches related to these problems. The book also reports advances on classic but difficult problems in HMMs such as inference and feature selection and describes real-world applications of HMMs from several domains. The book pertains to researchers and graduate students, who will gain a clear view of recent developments related to HMMs and their applications.
Hidden Markov Models in Finance
Hidden Markov Models in Finance - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hidden Markov Models in Finance write by Rogemar S. Mamon. This book was released on 2007-04-26. Hidden Markov Models in Finance available in PDF, EPUB and Kindle. A number of methodologies have been employed to provide decision making solutions globalized markets. Hidden Markov Models in Finance offers the first systematic application of these methods to specialized financial problems: option pricing, credit risk modeling, volatility estimation and more. The book provides tools for sorting through turbulence, volatility, emotion, chaotic events – the random "noise" of financial markets – to analyze core components.
Hidden Markov Models: Applications In Computer Vision
Hidden Markov Models: Applications In Computer Vision - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hidden Markov Models: Applications In Computer Vision write by Horst Bunke. This book was released on 2001-06-04. Hidden Markov Models: Applications In Computer Vision available in PDF, EPUB and Kindle. Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).
The Application of Hidden Markov Models in Speech Recognition
The Application of Hidden Markov Models in Speech Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Application of Hidden Markov Models in Speech Recognition write by Mark Gales. This book was released on 2008. The Application of Hidden Markov Models in Speech Recognition available in PDF, EPUB and Kindle. The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Markov Models for Pattern Recognition
Markov Models for Pattern Recognition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Markov Models for Pattern Recognition write by Gernot A. Fink. This book was released on 2014-01-14. Markov Models for Pattern Recognition available in PDF, EPUB and Kindle. This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.
