Neural Dynamics for Time-Varying Problems: Advances and Applications (時間變化問題的神經動力學：進展與應用)

Jin, Long, Wei, Lin, LV, Xin

Neural Dynamics for Time-Varying Problems: Advances and Applications
  • 出版商: Springer
  • 出版日期: 2024-10-02
  • 售價: $7,150
  • 貴賓價: 9.5 折 $6,793
  • 語言: 英文
  • 頁數: 202
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031685938
  • ISBN-13: 9783031685934

    • 海外代購書籍(需單獨結帳)

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商品描述

This book mainly presents methods based on neural dynamics for the time-varying problems with applications, together with the corresponding theoretical analysis, simulative examples, and physical experiments. Based on these methods, their applications include motion planning of redundant manipulators, filter design, winner-take-all operation, multiple-input multiple-output system configuration, multi-linear tensor equation solving, and manipulability optimization are also presented. In this book, we present the design, proposal, development, analysis, modeling, and simulation of various neural dynamic models, along with their respective applications including motion planning of redundant manipulators, filter design, winner-take-all operation, multiple-input multiple-output system configuration, multi-linear tensor equation solving, and manipulability optimization. Specifically, starting from the top-level considerations of hardware implementation, we integrate computational intelligence methods and control theory to design a series of dynamic and noise-resistant discrete neural dynamic methods. The research work not only owns the theoretical guarantee on its convergence, noise resistance, and accuracy, but demonstrate the effectiveness and robustness in solving various optimization and equation solving problems, particularly in handling time-varying problems and noise perturbations. Moreover, by reducing complexity and avoiding matrix inversion operations, the models' feasibility and practicality are further enhanced.

商品描述(中文翻譯)

本書主要介紹基於神經動力學的方法，針對時間變化的問題及其應用，並提供相應的理論分析、模擬範例和實驗。基於這些方法，其應用包括冗餘機器人的運動規劃、濾波器設計、贏者全拿操作、多輸入多輸出系統配置、多線性張量方程求解以及可操作性優化等。本書中，我們展示了各種神經動力學模型的設計、提案、開發、分析、建模和模擬，並介紹了其各自的應用，包括冗餘機器人的運動規劃、濾波器設計、贏者全拿操作、多輸入多輸出系統配置、多線性張量方程求解以及可操作性優化。具體而言，從硬體實現的高層考量出發，我們整合計算智能方法和控制理論，設計出一系列動態且抗噪聲的離散神經動力學方法。這項研究不僅在收斂性、抗噪聲性和準確性上具有理論保證，還展示了在解決各種優化和方程求解問題中的有效性和穩健性，特別是在處理時間變化問題和噪聲擾動方面。此外，通過降低複雜性和避免矩陣反演操作，進一步增強了模型的可行性和實用性。

作者簡介

Long Jin (Senior Member, IEEE) received the B.E. degree in automation and the Ph.D. degree in information and communication engineering from Sun Yat-sen University, Guangzhou, China, in 2011 and 2016, respectively. He underwent postdoctoral training with the Department of Computing, The Hong Kong Polytechnic University, Hong Kong, from 2016 to 2017. In 2017, he was a Professor of Computer Science and Engineering with the School of Information Science and Engineering, Lanzhou University, Lanzhou, China. From 2023 to 2024, he is serving as a Visiting Professor with The City University of Hong Kong, Hong Kong. He has published more than 90 papers in IEEE TRANSACTIONS journals. His current research interests include neural networks, optimization, intelligent computing, and robotics. Prof. Jin currently serves as an Associate Editor for IEEE TRANSACTIONS ON INTELLIGENT VEHICLES and IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS. Besides, he holds the position of Outstanding Young Editorial Board Member for the IEEE/CAA JOURNAL OF AUTOMATICA SINICA.

Lin Wei received the B.E. degree in electronic and information engineering from the Beijing Institute of Technology, Beijing, China, in 2018; and her Ph.D. degree in computer application technology from Lanzhou University in Lanzhou University. Her research interests include neural networks and robotics. She has published more than 12 scientific papers as author or co-author (including 7 IEEE-transaction papers).

Xin Lv received her B.S. degree in electronic information science and technology from Lanzhou University, Lanzhou, China, in 2003; and her M.S. degree in information and communication engineering and Ph.D. degree in radio physics from Lanzhou University, in 2006 and 2015, respectively. Currently, she is a lecturer in the School of Information Science and Engineering at Lanzhou University. Her research interests include machine learning, neural networks and optimization.

作者簡介(中文翻譯)

龍金（IEEE 高級會員）於2011年和2016年分別獲得中國廣州中山大學自動化學士學位及信息與通信工程博士學位。他於2016年至2017年在香港理工大學計算機系進行博士後訓練。2017年，他成為中國蘭州大學信息科學與工程學院的計算機科學與工程教授。從2023年到2024年，他擔任香港城市大學的訪問教授。他在IEEE TRANSACTIONS期刊上發表了90多篇論文。他目前的研究興趣包括神經網絡、優化、智能計算和機器人技術。龍教授目前擔任IEEE TRANSACTIONS ON INTELLIGENT VEHICLES和IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS的副編輯。此外，他還擔任IEEE/CAA JOURNAL OF AUTOMATICA SINICA的傑出青年編輯委員。

林瑋於2018年獲得中國北京理工大學電子與信息工程學士學位，並在蘭州大學獲得計算機應用技術博士學位。她的研究興趣包括神經網絡和機器人技術。她作為作者或共同作者發表了12篇以上的科學論文（包括7篇IEEE交易論文）。

呂欣於2003年獲得中國蘭州大學電子信息科學與技術學士學位，並於2006年和2015年分別獲得信息與通信工程碩士學位及無線物理博士學位。目前，她是蘭州大學信息科學與工程學院的講師。她的研究興趣包括機器學習、神經網絡和優化。

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