Regularized System Identification (Record no. 200457391)

MARC details
000 -LEADER
fixed length control field 04425nam a22006375i 4500
003 - CONTROL NUMBER IDENTIFIER
control field TR-AnTOB
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20231124090942.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220513s2022 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783030958602
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-030-95860-2
Source of number or code doi
040 ## - CATALOGING SOURCE
Original cataloging agency TR-AnTOB
Language of cataloging eng
Description conventions rda
Transcribing agency TR-AnTOB
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title İngilizce
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA402
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQM
Source bicssc
Subject category code COM004000
Source bisacsh
Subject category code UYQM
Source thema
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) QA402EBK
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Pillonetto, Gianluigi.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Regularized System Identification
Medium [electronic resource] :
Remainder of title Learning Dynamic Models from Data /
Statement of responsibility, etc. by Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, Lennart Ljung.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2022.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Cham :
Name of producer, publisher, distributor, manufacturer Springer International Publishing :
-- Imprint: Springer,
Date of production, publication, distribution, manufacture, or copyright notice 2022.
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
490 1# - SERIES STATEMENT
Series statement Communications and Control Engineering,
International Standard Serial Number 2197-7119
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 1. Bias -- Chapter 2. Classical System Identification -- Chapter 3. Regularization of Linear Regression Models -- Chapter 4. Bayesian Interpretation of Regularization -- Chapter 5. Regularization for Linear System Identification -- Chapter 6. Regularization in Reproducing Kernel Hilbert Spaces -- Chapter 7. Regularization in Reproducing Kernel Hilbert Spaces for Linear System Identification -- Chapter 8. Regularization for Nonlinear System Identification -- Chapter 9. Numerical Experiments and Real-World Cases.
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open Access
520 ## - SUMMARY, ETC.
Summary, etc. 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 Regularized System Identification will be of interest to a variety of researchers and practitioners in the areas of control systems, machine learning, statistics, and data science. In many ways, this book is a complement and continuation of the much-used text book L. Ljung, System Identification, 978-0-13-656695-3. This is an open access book.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Machine learning.
Topical term or geographic name entry element Control engineering.
Topical term or geographic name entry element System theory.
Topical term or geographic name entry element Statistics .
Topical term or geographic name entry element Control theory.
Topical term or geographic name entry element Machine Learning.
Topical term or geographic name entry element Control and Systems Theory.
Topical term or geographic name entry element Complex Systems.
Topical term or geographic name entry element Bayesian Inference.
Topical term or geographic name entry element Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Topical term or geographic name entry element Systems Theory, Control .
653 #0 - INDEX TERM--UNCONTROLLED
Uncontrolled term System identification
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Chen, Tianshi.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
Personal name Chiuso, Alessandro.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
Personal name De Nicolao, Giuseppe.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
Personal name Ljung, Lennart.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Communications and Control Engineering,
International Standard Serial Number 2197-7119
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-3-030-95860-2">https://doi.org/10.1007/978-3-030-95860-2</a>
Materials specified Springer eBooks
Public note Online access link to the resource
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type E-Book

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