| 书目名称 | Efficient Online Learning Algorithms for Total Least Square Problems | | 编辑 | Xiangyu Kong,Dazheng Feng | | 视频video | | | 概述 | Developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering.Reviews the basic TLS algorithms and derives novel method with detailed steps.Provides detailed | | 丛书名称 | Engineering Applications of Computational Methods | | 图书封面 |  | | 描述 | This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors’ latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided in this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors’ latest achievem | | 出版日期 | Book 2024 | | 关键词 | TLS; Total Least Square; Orthogonal Regression; Neural-Based Orthogonal Regression; the Errors-in-varian | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-97-1765-1 | | isbn_softcover | 978-981-97-1767-5 | | isbn_ebook | 978-981-97-1765-1Series ISSN 2662-3366 Series E-ISSN 2662-3374 | | issn_series | 2662-3366 | | copyright | Science Press 2024 |
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发表于 2025-3-21 17:03:21
