Hidden Markov Models and Applications (1st ed. 2022) (Unsupervised and Semi-Supervised Learning)

By: Nizar Bouguila and Wentao Fan and Manar Amayri

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9783030991425
Related ISBNs:: 9783030991418
Publisher:: Springer International Publishing
Date of Addition:: 06/26/22
Copyrighted By:: The Editor
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Computers and Internet, Technology, Mathematics and Statistics
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.
Edited by:: Nizar Bouguila
Edited by:: Wentao Fan
Edited by:: Manar Amayri