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Springer Nonlinear Predictive Control Using Wiener Models 389

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Description

Expand your technical library with Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures. Published by Springer as part of the Studies in Systems, Decision and Control series (Volume 389), this academic text focuses on advanced control methodologies. This volume provides a specialized look at computationally efficient approaches for both polynomial and neural structures within nonlinear predictive control. It is designed for researchers and professionals seeking deep technical knowledge in systems and decision control. By integrating Wiener models into predictive frameworks, this book addresses complex control challenges with a focus on efficiency and structure. Whether you are studying system theory or implementing advanced control algorithms, this Springer publication serves as a dedicated reference for your technical studies.

Key Features

Part of the Studies in Systems, Decision and Control series, providing a specialized academic framework.

Focuses on computationally efficient approaches for polynomial and neural structures.

Published by Springer, a leading name in technical and scientific literature.

Specifically addresses nonlinear predictive control using Wiener models.

Serves as a professional reference for advanced systems and decision control studies.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
23 September 2022
Listed Since
26 August 2022

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