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Hidden Markov Models and Applications. 2022 ed.
・ISBN 978-3-030-99144-9 paper EUR 129.99
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| 著者・編者 | Bouguila, Nizar / Fan, Wentao / Amayri, Manar (eds.), |
|---|---|
| シリーズ | (Unsupervised and Semi-Supervised Learning) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2023 |
| ページ数 | 298 pp. |
| 言語 | ENG |
| ニュース番号 | <A01-97993> |
解説
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.