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Zeroing Neural Networks

Finite-time Convergence Design, Analysis and Applications
By Lei Jia and Lin Xiao
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Book Hero Magic crafted this summary to help describe this book. While it's new and still learning, it may not be perfect - your feedback is welcome! Summary
Zeroing Neural Networks explores finite-time zeroing neural networks (FTZNN) as cutting-edge tools for solving discretized sensor-driven time-varying matrix problems. The book thoroughly covers theory, design, and practical applications of FTZNN models across various computational challenges such as the Lyapunov equation and matrix inversion. Divided into eight parts, it includes modelling methods, nonlinear activation functions, theoretical analysis, and extensive simulations, all illustrated with tables and examples to clarify advantages and noise tolerance.
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Format: Hardback
$27499
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?

Zeroing Neural Networks is ideal for scientists, researchers, academic lecturers, and postgraduate students specialising in neurocomputing and intelligent control. It also serves as a valuable reference for engineers and professionals engaged in robotics, control theory, and real-time computational problem solving.

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Book Hero Magic formatted this description to make it easier to read. While it's new and still learning, it may not be perfect - your feedback is welcome! Description

Zeroing Neural Networks describes the theoretical and practical aspects of finite-time ZNN methods for solving an array of computational problems.

Zeroing Neural Networks (ZNN) have become essential tools for solving discretised sensor-driven time-varying matrix problems in engineering, control theory, and on-chip applications for robots. Building on the original ZNN model, finite-time zeroing neural networks (FTZNN) enable efficient, accurate, and predictive real-time computations. Setting up discretised FTZNN algorithms for different time-varying matrix problems requires distinct steps.

Zeroing Neural Networks provides in-depth information on the finite-time convergence of ZNN models in solving computational problems. Divided into eight parts, this comprehensive resource covers modelling methods, theoretical analysis, computer simulations, nonlinear activation functions, and more. Each part focuses on a specific type of time-varying computational problem, such as the application of FTZNN to the Lyapunov equation, linear matrix equation, and matrix inversion. Throughout the book, tables explain the performance of different models, while numerous illustrative examples clarify the advantages of each FTZNN method. In addition, the book:

  • Describes how to design, analyse, and apply FTZNN models for solving computational problems
  • Presents multiple FTZNN models for solving time-varying computational problems
  • Details the noise-tolerance of FTZNN models to maximise the adaptability of FTZNN models to complex environments
  • Includes an introduction, problem description, design scheme, theoretical analysis, illustrative verification, application, and summary in every chapter

Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications is an essential resource for scientists, researchers, academic lecturers, and postgraduates in the field, as well as a valuable reference for engineers and other practitioners working in neurocomputing and intelligent control.

Book Details

INFORMATION

ISBN: 9781119985990

Publisher: John Wiley & Sons Inc

Format: Hardback

Date Published: 04 November 2022

Country: United States

Imprint: Wiley-IEEE Press

Audience: Tertiary education, Professional and scholarly

DIMENSIONS

Weight: 835g

Pages: 432

Collections

Computing & Technology Education & Reference Engineering, Technology & Agriculture Lei Jia Lin Xiao Non-Fiction

About the Author

LIN XIAO, PhD, is a Professor in the College of Information Science and Engineering at Hunan Normal University, Changsha, China. He has authored more than 100 papers in international conferences and journals, including IEEE-TCYB, IEEE-TII, IEEE-TSMCS. Professor Xiao is Associate Editor of IEEE-TNNLS.

LEI JIA is a PhD degree candidate in Operations Research and Control in the College of Mathematics and Statistics at Hunan Normal University, Changsha, China. She has authored or co-authored more than 20 scientific articles, including 13 IEEE-transaction papers.

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