Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring
Language: English
Published by Elsevier, 2025
- Softcover
- New

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In English.
Seller Inventory # ria9780443334863_new
- Title
- Sparsity Measures and their Signal Processing Applications for Machine Condition Monitoring
- Author
- Wang PhD, Dong; Hou B.Eng, Bingchang
- Publisher
- Elsevier
- Publication year
- 2025
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0443334862
- ISBN 13
- 9780443334863
- Item weight
- 430 grams
- Provides the background, roadmaps and detailed discussion of newly designed sparsity measures and their advanced signal processing technologies for machine condition monitoring and fault diagnosis
- Covers new theories, advanced technologies, and the latest contributions in the field of machine condition monitoring and fault diagnosis
- Particularly focuses on newly advanced sparsity measures for fault signature quantification, classic and advanced sparsity measures–based signal processing technologies and sparsity measures using data-driven framework–based signal processing technologies
- Provides experimental and real-world practical validation cases, including newly advanced sparsity measures and their advanced signal processing technologies
"Synopsis" may belong to another edition of this title.
About the Author
Bingchang Hou received his B.Eng. degree in Mechanical Engineering from Chongqing University, Chongqing, China, in 2020. Since Sep. 2020, he is pursuing his Ph.D. degree in Department of Industrial Engineering and Management, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. His research interests include machine condition monitoring and fault diagnosis, prognostics and health management, sparsity measures, signal processing, and machine learning
"About the title" may belong to another edition of this title.
Ria Christie Collections
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AbeBooks seller since March 25, 2015
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