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Neural network modeling and identifi...

Tiumentsev, Yury V.

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Neural network modeling and identification of dynamical systems

Record Type:	Electronic resources : Monograph/item
Title/Author:	Neural network modeling and identification of dynamical systems/ Yury V. Tiumentsev, Mikhail V. Egorchev.
Author:	Tiumentsev, Yury V.
other author:	Egorchev, Mikhail.
Published:	London :Academic Press, : 2019.,
Description:	1 online resource
Notes:	Includes index.
Subject:	Neural networks (Computer science) -
Online resource:	https://www.sciencedirect.com/science/book/9780128152546
ISBN:	9780128154304 (electronic bk.)

Neural network modeling and identification of dynamical systems
Tiumentsev, Yury V.

Neural network modeling and identification of dynamical systems[electronic resource] /Yury V. Tiumentsev, Mikhail V. Egorchev. - London :Academic Press,2019. - 1 online resource

Includes index.

A new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and trainingOffers application examples of dynamic neural network technologies, primarily related to aircraftProvides an overview of recent achievements and future needs in this area

ISBN: 9780128154304 (electronic bk.)Subjects--Topical Terms:

532070
Neural networks (Computer science)
Index Terms--Genre/Form:

542853
Electronic books.

LC Class. No.: QA76.87

Dewey Class. No.: 006.32

Neural network modeling and identification of dynamical systems
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245 1 0 $a Neural network modeling and identification of dynamical systems $h [electronic resource] / $c Yury V. Tiumentsev, Mikhail V. Egorchev.
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300 $a 1 online resource
500 $a Includes index.
520 $a A new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and trainingOffers application examples of dynamic neural network technologies, primarily related to aircraftProvides an overview of recent achievements and future needs in this area
588 0 $a Online resource; title from PDF title page (EBSCO, viewed May 29, 2019).
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655 0 $a Electronic books. $2 lcsh $3 542853
700 1 $a Egorchev, Mikhail. $3 3510051
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