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Difference equations and machine learning

Record Type:	Electronic resources : Monograph/item
Title/Author:	Difference equations and machine learningby Dušan Stipanović.
Author:	Stipanović, Dušan.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xii, 143 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Difference equations.
Online resource:	https://doi.org/10.1007/978-3-032-00910-4
ISBN:	9783032009104$q(electronic bk.)

Difference equations and machine learning
Stipanović, Dušan.

Difference equations and machine learning[electronic resource] /by Dušan Stipanović. - Cham :Springer Nature Switzerland :2025. - xii, 143 p. :ill., digital ;24 cm. - Synthesis lectures on mathematics & statistics,1938-1751. - Synthesis lectures on mathematics & statistics..

Introduction -- Linear Difference Equations -- Nonlinear Difference Equations -- Stability and Chaotic Behaviors of Difference Equations -- Control of Difference Equations -- Applications to Neural Networks and Machine Learning -- Conclusions.

This book presents in-depth explanations of well-known and recognized behaviors of neural networks in machine learning. In addition, the author provides novel technical analyses of behaviors of discrete-time dynamical systems modeled as difference equations. These analyses and their outcomes are closely related to models of very well-known neural networks such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks, which are widely used in machine learning and artificial intelligence (AI) applications. The author also discusses difference equations and their relevance to neural networks, machine learning, and AI. In addition, this book: Includes characterizations of difference equations and technical prospectives of discrete-time systems Provides new insights into the dynamical behaviors of some of the most popular neural networks used in machine learning Discusses novel technical analyses of discrete-time dynamical systems modeled as difference equations.

ISBN: 9783032009104$q(electronic bk.)

Standard No.: 10.1007/978-3-032-00910-4doiSubjects--Topical Terms:

185958
Difference equations.

LC Class. No.: QA431 / .S75 2025

Dewey Class. No.: 515.45

Difference equations and machine learning
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505 0 $a Introduction -- Linear Difference Equations -- Nonlinear Difference Equations -- Stability and Chaotic Behaviors of Difference Equations -- Control of Difference Equations -- Applications to Neural Networks and Machine Learning -- Conclusions.
520 $a This book presents in-depth explanations of well-known and recognized behaviors of neural networks in machine learning. In addition, the author provides novel technical analyses of behaviors of discrete-time dynamical systems modeled as difference equations. These analyses and their outcomes are closely related to models of very well-known neural networks such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) neural networks, which are widely used in machine learning and artificial intelligence (AI) applications. The author also discusses difference equations and their relevance to neural networks, machine learning, and AI. In addition, this book: Includes characterizations of difference equations and technical prospectives of discrete-time systems Provides new insights into the dynamical behaviors of some of the most popular neural networks used in machine learning Discusses novel technical analyses of discrete-time dynamical systems modeled as difference equations.
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