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Regularized System Identification: Learning Dynamic Models from Data (Communications and Control Engineering) free ebook download

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Control Theory

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Catalogue

Author(s):	Gianluigi Pillonetto

Date:	2021	Format:	7z	Language:	English	ISBN/ASIN:	3030958590
Pages:	401	OCR:		Quality:		ISBN13:
Uploader:	maveriks	Upload Date:	5/23/2022 7:09:06 AM

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This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the power of machine learning without losing sight of the system-theoretical principles of black-box identification. The authors reformulation of the identification problem in the light of regularization theory not only offers new insight on classical questions, but paves the way to new and powerful algorithms for a variety of linear and nonlinear problems. Regression methods such as regularization networks and support vector machines are the basis of techniques that extend the function-estimation problem to the estimation of dynamic models. Many examples, also from real-world applications, illustrate the comparative advantages of the new nonparametric approach with respect to classic parametric prediction error methods.
The challenges it addresses lie at the intersection of several disciplines so 
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3122364	Book	https://nitro.download/view/4FF8E53A7BA3...		0.00	maveriks

Tags: Communications Control Data Dynamic Engineering Identification Learning Models Regularized System

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Regularized System Identification: Learning Dynamic Models from Data (Communications and Control Engineering) free ebook download

Category: Control Theory

Description: Click to see full description

Category:
Control Theory