Elliott David L. (EN) — Neural Systems for Control

Тут можно читать онлайн книгу Elliott David L. (EN) - Neural Systems for Control - бесплатно полную версию (целиком). Жанр книги: Иностранная литература. Вы можете прочесть полную версию (весь текст) онлайн без регистрации и смс на сайте Lib-King.Ru (Либ-Кинг) или прочитать краткое содержание, аннотацию (предисловие), описание и ознакомиться с отзывами (комментариями) о произведении.

Neural Systems for Control
Язык книги: Английский
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Neural Systems for Control краткое содержание

Neural Systems for Control - описание и краткое содержание, автор Elliott David L. (EN), читать бесплатно онлайн на сайте электронной библиотеки Lib-King.Ru.

Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance.Key Features* Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory* Represents the most up-to-date developments in this rapidly growing application area of neural networks* Takes a new and novel approach to system identification and synthesis

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