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Titlebook: Breath Analysis for Medical Applications; David Zhang,Dongmin Guo,Ke Yan Book 2017 Springer Nature Singapore Pte Ltd. 2017 Breath signal D

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發(fā)表于 2025-3-21 17:43:34 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Breath Analysis for Medical Applications
影響因子2023David Zhang,Dongmin Guo,Ke Yan
視頻videohttp://file.papertrans.cn/191/190635/190635.mp4
發(fā)行地址The first systematic and comprehensive book on breath analysis and its medical applications.Covers all aspects of breath signal processing, including acquisition, preprocessing, classification, and ty
圖書封面Titlebook: Breath Analysis for Medical Applications;  David Zhang,Dongmin Guo,Ke Yan Book 2017 Springer Nature Singapore Pte Ltd. 2017 Breath signal D
影響因子.This book describes breath signal processing technologies and their applications in medical sample classification and diagnosis. First, it provides a comprehensive introduction to breath signal acquisition methods, based on different kinds of chemical sensors, together with the optimized selection and fusion acquisition scheme. It then presents preprocessing techniques, such as drift removing and feature extraction methods, and uses case studies to explore the classification methods. Lastly it discusses promising research directions and potential medical applications of computerized breath diagnosis. It is a valuable interdisciplinary resource for researchers, professionals and postgraduate students working in various fields, including breath diagnosis, signal processing, pattern recognition, and biometrics..
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發(fā)表于 2025-3-21 20:32:08 | 只看該作者
Visionsarbeit von Walt Disney lernen-RFE and other typical algorithms. An ensemble method is further studied to improve the stability of the proposed method. By statistically analyzing the features’ rankings, some knowledge is obtained, which can guide future design of e-noses and feature extraction algorithms.
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Feature Selection and Analysis on Correlated Breath Data-RFE and other typical algorithms. An ensemble method is further studied to improve the stability of the proposed method. By statistically analyzing the features’ rankings, some knowledge is obtained, which can guide future design of e-noses and feature extraction algorithms.
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including acquisition, preprocessing, classification, and ty.This book describes breath signal processing technologies and their applications in medical sample classification and diagnosis. First, it provides a comprehensive introduction to breath signal acquisition methods, based on different kinds
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https://doi.org/10.1007/978-3-322-87042-1h analysis device, and of the design of specific pattern recognition algorithm for breath analysis. This is followed by a statement of the objective of the research, a brief summary of the work, and a general outline of the overall structure of the present study.
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