東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Advanced signal processing = decompo...

Zhang, Yuning.

FindBook

Google Book

Amazon

博客來

Advanced signal processing = decomposition, entropy, and machine learning /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advanced signal processing/ by Yuning Zhang ... [et al.].
其他題名:	decomposition, entropy, and machine learning /
其他作者:	Zhang, Yuning.
出版者:	Cham :Springer Nature Switzerland : : 2025.,
面頁冊數:	viii, 83 p. :ill. (some col.), digital ;24 cm.
內容註:	Introduction -- Signal decomposition methods -- Entropy analysis methods -- Machine learning methods -- Signal denoising applications -- Pattern recognition applications -- Conclusion.
Contained By:	Springer Nature eBook
標題:	Signal processing. -
電子資源:	https://doi.org/10.1007/978-3-032-11854-7
ISBN:	9783032118547

Advanced signal processing = decomposition, entropy, and machine learning /
Advanced signal processingdecomposition, entropy, and machine learning /[electronic resource] :by Yuning Zhang ... [et al.]. - Cham :Springer Nature Switzerland :2025. - viii, 83 p. :ill. (some col.), digital ;24 cm. - SpringerBriefs in energy,2191-5539. - SpringerBriefs in energy..

Introduction -- Signal decomposition methods -- Entropy analysis methods -- Machine learning methods -- Signal denoising applications -- Pattern recognition applications -- Conclusion.

This brief explores advanced signal processing techniques, focusing on signal decomposition, entropy analysis, and machine learning, with applications in energy-related fields such as hydroturbines, wind turbines, and power grids. It provides a detailed overview of methods for signal denoising and pattern recognition, covering techniques like wavelet transform, empirical mode decomposition, permutation entropy, and deep learning models. Through real-world engineering case studies, the book demonstrates how these methods enhance data analysis, improve fault detection, and optimize system performance, making it a valuable resource for researchers, engineers, and students in signal processing and mechanical engineering.

ISBN: 9783032118547

Standard No.: 10.1007/978-3-032-11854-7doiSubjects--Topical Terms:

533904
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.3822

Advanced signal processing = decomposition, entropy, and machine learning /
LDR:01963nmm a2200337 a 4500 001 2422679
003 DE-He213
005 20260102120824.0
006 m d
007 cr nn 008maaau
008 260505s2025 sz s 0 eng d
020 $a 9783032118547 $q (electronic bk.)
020 $a 9783032118530 $q (paper)
024 7 $a 10.1007/978-3-032-11854-7 $2 doi
035 $a 978-3-032-11854-7
040 $a GP $c GP
041 0 $a eng
050 4 $a TK5102.9
072 7 $a THRD $2 bicssc
072 7 $a TEC031020 $2 bisacsh
072 7 $a THY $2 thema
082 0 4 $a 621.3822 $2 23
090 $a TK5102.9 $b .A244 2025
245 0 0 $a Advanced signal processing $h [electronic resource] : $b decomposition, entropy, and machine learning / $c by Yuning Zhang ... [et al.].
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2025.
300 $a viii, 83 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a SpringerBriefs in energy, $x 2191-5539
505 0 $a Introduction -- Signal decomposition methods -- Entropy analysis methods -- Machine learning methods -- Signal denoising applications -- Pattern recognition applications -- Conclusion.
520 $a This brief explores advanced signal processing techniques, focusing on signal decomposition, entropy analysis, and machine learning, with applications in energy-related fields such as hydroturbines, wind turbines, and power grids. It provides a detailed overview of methods for signal denoising and pattern recognition, covering techniques like wavelet transform, empirical mode decomposition, permutation entropy, and deep learning models. Through real-world engineering case studies, the book demonstrates how these methods enhance data analysis, improve fault detection, and optimize system performance, making it a valuable resource for researchers, engineers, and students in signal processing and mechanical engineering.
650 0 $a Signal processing. $3 533904
650 1 4 $a Energy Grids and Networks. $3 3592502
650 2 4 $a Hydroenergy. $3 3592798
650 2 4 $a Electrical and Electronic Engineering. $3 3591890
650 2 4 $a Machine Learning. $3 3382522
700 1 $a Zhang, Yuning. $3 3790738
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in energy. $3 1570022
856 4 0 $u https://doi.org/10.1007/978-3-032-11854-7
950 $a Energy (SpringerNature-40367)