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Security of e-Systems and Computer Networks, Mohammad Obaidat


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Цена: 12830.00р.
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Автор: Mohammad Obaidat
Название:  Security of e-Systems and Computer Networks
Перевод названия: Мохаммад Обайдат: Безопасность E-систем и компьютерных сетей
ISBN: 9780521837644
Издательство: Cambridge Academ
Классификация:

ISBN-10: 0521837642
Обложка/Формат: Hardback
Страницы: 386
Вес: 0.90 кг.
Дата издания: 14.06.2007
Язык: English
Иллюстрации: 43 line figures 43 figures
Размер: 255 x 182 x 24
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Presents fundamental concepts and tools of e-based security. The core areas of security are covered in detail and the major trends, challenges and applications discussed. Technically oriented with practical examples, this book is suitable for practitioners in network security, and graduate students and researchers in telecommunications and computer science.


Control of Electric Machine Drive Systems

Автор: Sul
Название: Control of Electric Machine Drive Systems
ISBN: 0470590793 ISBN-13(EAN): 9780470590799
Издательство: Wiley
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Цена: 20901.00 р.
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Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.

Neural Networks for Modelling and Control of Dynamic Systems / A Practitioner`s Handbook

Автор: Norgaard M., Ravn O., Poulsen N.K., Hansen L.K.
Название: Neural Networks for Modelling and Control of Dynamic Systems / A Practitioner`s Handbook
ISBN: 1852332271 ISBN-13(EAN): 9781852332273
Издательство: Springer
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Цена: 11179.00 р.
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Описание: The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.


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