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Titlebook: Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis; Xiangyu Kong,Jiayu Luo,Xiaowei Feng Book 2024 Science

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书目名称Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis
编辑Xiangyu Kong,Jiayu Luo,Xiaowei Feng
视频video
概述Focuses on the quality-related process monitoring of different situations, with MSPC-based models such as PCA, PLS.Reviews the basic model and derives novel method with detailed steps.Provides detaile
丛书名称Engineering Applications of Computational Methods
图书封面Titlebook: Process Monitoring and Fault Diagnosis Based on Multivariable Statistical Analysis;  Xiangyu Kong,Jiayu Luo,Xiaowei Feng Book 2024 Science
描述This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, this book 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 by 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 a
出版日期Book 2024
关键词MSPC-based methods; Process monitoring; Fault diagnosis; Quality-related time-varying process monitorin
版次1
doihttps://doi.org/10.1007/978-981-99-8775-7
isbn_softcover978-981-99-8777-1
isbn_ebook978-981-99-8775-7Series ISSN 2662-3366 Series E-ISSN 2662-3374
issn_series 2662-3366
copyrightScience Press 2024
The information of publication is updating

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