| 书目名称 | Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint | | 编辑 | Mark K. Hinders | | 视频video | | | 概述 | Presents the dynamic wavelet fingerprint technique of identifying machine learning features.Discusses numerous real-world applications, including in the medical, vehicle and wireless technology.Struct | | 图书封面 |  | | 描述 | .This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. .Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint. begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader’s area of interest, or read together to provide a comprehensive overview of the topic. .Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autono | | 出版日期 | Book 2020 | | 关键词 | Pattern Classification; Wavelet Fingerprints; Lamb Waves; Ultrasound; Radio Frequency Identification; Aut | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-030-49395-0 | | isbn_softcover | 978-3-030-49397-4 | | isbn_ebook | 978-3-030-49395-0 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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发表于 2025-3-21 16:34:35
