Автор: Lin Xiao, Lei Jia Название: Zeroing Neural Networks: Finite-time Convergence Design, Analysis and Applications ISBN: 1119985994 ISBN-13(EAN): 9781119985990 Издательство: Wiley Рейтинг: Цена: 111930.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: 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 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 discretized 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 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 FTZNN 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 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.
Автор: Amit Kumar Tyagi, Ajith Abraham Название: Recurrent neural networks : ISBN: 1032081643 ISBN-13(EAN): 9781032081649 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book comprehensively covers concepts of recurrent neural networks and discusses practical issues such as predictability and nonlinearity detecting. It will an ideal text for senior undergraduate, graduate students, researchers, and professionals in the fields of electrical, electronics and communication, and computer engineering.
Автор: Maciej Krawczak Название: Multilayer Neural Networks ISBN: 3319002473 ISBN-13(EAN): 9783319002477 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book shows that a multilayer neural network can be considered as a multistage system, and that the learning of this class of neural networks can be treated as a special sort of the optimal control problem.
Название: Computational social psychology ISBN: 113895165X ISBN-13(EAN): 9781138951655 Издательство: Taylor&Francis Рейтинг: Цена: 54090.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Computational Social Psychology showcases a new approach to social psychology that enables theorists and researchers to implemented and test models of processes using the power of high speed computing technology and sophisticated software.
Автор: Chua Название: Cellular Neural Networks and Visual Computing ISBN: 0521652472 ISBN-13(EAN): 9780521652476 Издательство: Cambridge Academ Рейтинг: Цена: 139390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is a unique undergraduate level textbook on Cellular Nonlinear/neural Networks (CNN) technology. The many examples and excercises, including a simulator accessible via the Internet, make this book an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of backgrounds.
Автор: Saad Название: On-Line Learning in Neural Networks ISBN: 0521652634 ISBN-13(EAN): 9780521652636 Издательство: Cambridge Academ Рейтинг: Цена: 124610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: On-line learning is one of the most commonly used techniques for training large layered networks. Traditional methods have been recently complemented by ones from statistical physics and Bayesian statistics to provide more insight and deeper understanding of existing algorithms. This book presents a coherent picture of the state-of-the-art.
Автор: Gil-Aluja Jaime Et Al Название: Methods For Decision Making In An Uncertain Environment - Proceedings Of The Xvii Sigef Congress ISBN: 9814415766 ISBN-13(EAN): 9789814415767 Издательство: World Scientific Publishing Рейтинг: Цена: 158400.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Contains a selection of the papers presented at the XVII SIGEF Congress. This title is suitable for researchers and graduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments.
Автор: Madhumangal Pal, Sovan Samanta, Anita Pal Название: Handbook of Research on Advanced Applications of Graph Theory in Modern Society ISBN: 1522593802 ISBN-13(EAN): 9781522593805 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 219910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In the world of mathematics and computer science, technological advancements are constantly being researched and applied to ongoing issues. Setbacks in social networking, engineering, and automation are themes that affect everyday life, and researchers have been looking for new techniques in which to solve these challenges. Graph theory is a widely studied topic that is now being applied to real-life problems.
Advanced Applications of Graph Theory in Modern Society is an essential reference source that discusses recent developments on graph theory, as well as its representation in social networks, artificial neural networks, and many complex networks. The book aims to study results that are useful in the fields of robotics and machine learning and will examine different engineering issues that are closely related to fuzzy graph theory. Featuring research on topics such as artificial neural systems and robotics, this book is ideally designed for mathematicians, research scholars, practitioners, professionals, engineers, and students seeking an innovative overview of graphic theory.
Автор: Bruno Despres Название: Neural Networks and Numerical Analysis ISBN: 3110783126 ISBN-13(EAN): 9783110783124 Издательство: Walter de Gruyter Рейтинг: Цена: 185890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book uses numerical analysis as the main tool to investigate methods in machine learning and neural networks. The efficiency of neural network representations for general functions and for polynomial functions is studied in detail, together with an original description of the Latin hypercube method and of the ADAM algorithm for training. Furthermore, unique features include the use of Tensorflow for implementation session, and the description of on going research about the construction of new optimized numerical schemes.
Автор: Rios, Jorge D. Название: Neural Networks Modeling And Control ISBN: 0128170786 ISBN-13(EAN): 9780128170786 Издательство: Elsevier Science Рейтинг: Цена: 132500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control.
As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends.
Автор: Chakraborty, Debarati B Название: Granular video computing: with rough sets, deep learning and in iot ISBN: 981122711X ISBN-13(EAN): 9789811227110 Издательство: World Scientific Publishing Рейтинг: Цена: 84480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.
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