資料來源: Google Book
Wavelets in soft computing[electronic resource]
- 作者: Thuillard, Marc.
- 出版: Singapore : World Scientific c2023.
- 版本: 2nd ed.
- 稽核項: 1 online resource (320 p.) :ill.
- 叢書名: World Scientific series in robotics and intelligent systems ;v. 29
- 標題: Soft computing. , Wavelets (Mathematics)
- ISBN: 9811264031 , 9789811264030
- ISBN: 9789811263989 , 9811263981
- 試查全文@TNUA:
- 附註: Includes bibliographical references and index. Introduction to wavelet theory -- Preprocessing: the multiresolution approach -- Spline-based wavelets approximation and compression algorithms -- Automatic generation of a fuzzy system with wavelet-based methods and spline-based wavelets -- Nonparametric wavelet-based estimation and regression techniques -- Hybrid neural networks -- Multiresolution and deep neural networks -- Developing intelligent sensors with fuzzy logic and multiresolution analysis -- Multiresolution and wavelets in graphs, trees, and networks -- Genetic algorithms and multiresolution.
- 摘要: "The comprehensive compendium furnishes a quick and efficient entry point to many multiresolution techniques and facilitates the transition from an idea into a real project. It focuses on methods combining several soft computing techniques (fuzzy logic, neural networks, genetic algorithms) in a multiresolution framework. Illustrated with numerous vivid examples, this useful volume gives the reader the necessary theoretical background to decide which methods suit his/her needs. New materials and applications for multiresolution analysis are added, including notable research topics such as deep learning, graphs, and network analysis"--
- 電子資源: https://dbs.tnua.edu.tw/login?url=https://www.worldscientific.com/worldscibooks/10.1142/13074#t=toc
- 系統號: 005332057
- 資料類型: 電子書
- 讀者標籤: 需登入
- 引用網址: 複製連結
The comprehensive compendium furnishes a quick and efficient entry point to many multiresolution techniques and facilitates the transition from an idea into a real project. It focuses on methods combining several soft computing techniques (fuzzy logic, neural networks, genetic algorithms) in a multiresolution framework.Illustrated with numerous vivid examples, this useful volume gives the reader the necessary theoretical background to decide which methods suit his/her needs.New materials and applications for multiresolution analysis are added, including notable research topics such as deep learning, graphs, and network analysis.
來源: Google Book
來源: Google Book
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