Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications

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Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications

  • Author:Lei JiaLin Xiao
  • Length: 432 pages
  • Edition: 1
  • Publisher: Wiley-IEEE Press
  • Publication Date: 2022-11-22
  • ISBN-10: 1119985994
  • ISBN-13: 9781119985990
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    Book 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 discretized sensor-driven time-varying matrix problems in engineer帕图斯ing, control theory, and on-chip applications for robots. Building on the original ZNN model, finite-time zeroing neural networks (FTZNN) enable efficient, accurate, an天王d predictive real-time computations. Setting up discretized FTZNN algorithms for劳力士 different time-varying matrix problems requires distinct steps.

    Zeroing Neural Networksprovides in-depth information on the finite-time convergence of ZNN models in solving computational problems. Divided into eight parts, this comprehensive resource covers modeling 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, analyze, and apply FT波西塔诺ZNN models for solving computational problems
    • Presents multiple FTZNN models for solving time-varying computational problems
    • Details the noise-tolerance of FTZNN models to maximize 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 Netw宝珀orks: Finite-time Convergence Design, Analysis and Applicationsis 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.

    中文:

    书名:归零神经网络: 有限时间收敛设计,分析和应用

    归零神经网络

    描述了求解一系列计算问题的有限时间ZNN方法的理论和实践方面

    归零神经网络 (ZNN) 已成为解决工程,控制理论和机器人片上应用中离散化传感器驱动的时变矩阵问题的重要工具。在原始ZNN模型的基础上,有限时间归零神经网络 (FTZNN) 可实现高效,准确和预测性的实时计算。为不同的时变矩阵问题建立离散化的FTZNN算法需要不同的步骤。

    归零神经网络提供了有关ZNN模型在解决计算问题时的有限时间收敛的深入信息。该资源分为八个部分,涵盖建模方法,理论分析,计算机仿真,非线性激活函数等。每个部分都着重于一类特定的时变计算问题,例如将FTZNN应用于Lyapunov方程,线性矩阵方程和矩阵求逆。在本书中,表格解释了不同模型的性能,而许多说明性示例阐明了每种FTZNN方法的优点。此外,这本书:

    • 介绍如何设计、分析和应用FTZNN模型解决计算问题
    • 提出多个FTZNN模型求解时变计算问题
    • 详细介绍FTZNN模型的噪声容限,以最大程度地提高FTZNN模型对复杂环境的适应性
    • 包括引言、问题描述、设计方案、理论分析、说明性验证、应用和总结,在每一章

    归零神经网络: 有限时间收敛设计,分析和应用是该领域的科学家,研究人员,学术讲师和研究生的重要资源,也是工程师和其他从事神经计算和智能控制的从业人员的宝贵参考。

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