Mathematical Methods in Modern Complexity Science (Nonlinear Systems and Complexity, 33)

ISBN 10: 3030794113 / ISBN 13: 9783030794118

Published by Springer, 2022

About this Item

1st ed. 2022 edition NO-PA16APR2015-KAP.

Seller Inventory # 26388000932

Bibliographic Details

• Title: Mathematical Methods in Modern Complexity Science (Nonlinear Systems and Complexity, 33)
• Publisher: Springer
• Publication Date: 2022
• Language: English
• ISBN 10: 3030794113
• ISBN 13: 9783030794118
• Binding: Hardcover
• Condition: New

About this title

Synopsis

This book presents recent developments in nonlinear and complex systems. It provides recent theoretic developments and new techniques based on a nonlinear dynamical systems approach that can be used to model and understand complex behavior in nonlinear dynamical systems. It covers information theory, relativistic chaotic dynamics, data analysis, relativistic chaotic dynamics, solvability issues in integro-differential equations, and inverse problems for parabolic differential equations, synchronization and chaotic transient. Presents new concepts for understanding and modeling complex systems

 

 

About the Author

Dr J. A. Tenreiro Machado was born at 1957. He graduated with ‘Licenciatura’ (1980), PhD. (1989) and ‘Habilitation’ (1995), in Electrical and Computer Engineering at the University of Porto. During 1980-1998 he worked at the Dept. of Electrical and Computer Engineering of the University of Porto. Since 1998 he works at the Institute of Engineering, Polytechnic Institute of Porto, Dept. of Electrical Engineering. His research focuses on complex systems, nonlinear dynamics, fractional calculus, modeling, entropy, control, and evolutionary computing, as well as genomics. Prof. J. A. Tenreiro Machado is a member of the Editorial boards of several international journals, guest editor of Special Issues, and has about 1000 publications in journals, conferences, and books.

Dr.  Dimitri Volchenkov, an Associate Professor of Applied Mathematics, Mathematics and Statistics Department, Texas Tech University (USA) and a “Thousand talent plan of China” Professor in the Artificial Intelligence Key Laboratory of Sichuan Province, School of Automation and Information Engineering, Sichuan University of Science and Engineering (China). He is a qualified professor in France and Germany, admitted as “Nationally recognized Talent” of China, awarded by Cheung Kong Scholarship (China), Alexander von Humboldt and Volkswagen Fellowships (Germany), NATO/OTAN and C.N.R.S Fellowships (France), George Soros Foundation (USA) and Scientists Federal Awards (Russia). He is an expert in data analysis, complexity science, network theory, stochastic non-linear dynamics, control, and uncertainty in the real-world systems