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The Resource ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource)
ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource)
Resource Information
The item ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.This item is available to borrow from all library branches.
Resource Information
The item ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Boston University Libraries.
This item is available to borrow from all library branches.
 Summary
 This book presents an overview of the different errorsinvariables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a nontrivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuoustime models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on biascompensation; covariance matching methods; and prediction error and maximumlikelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. ErrorsinVariables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving overdetermined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.
 Language
 eng
 Edition
 1st ed. 2018.
 Extent
 XXVII, 485 p. 30 illus., 3 illus. in color.
 Contents

 Chapter 1. Introduction
 Chapter 2. The Static Case
 Chapter 3. The ErrorsinVariables Problem for Dynamic Systems
 Chapter 4. Identifiability Aspects
 Chapter 5. Modeling Aspects
 Chapter 6. Elementary Methods
 Chapter 7. Methods Based on BiasCompensation
 Chapter 8. Covariance Matching
 Chapter 9. Prediction Error and Maximum Likelihood Methods
 Chapter 10. Frequency Domain Methods
 Chapter 11. Total Least Squares
 Chapter 12. Methods for Periodic Data
 Chapter 13. Algorithmic Properties
 Chapter 14. Asymptotic Distributions
 Chapter 15. ErrorsinVariables Problems in Practice
 Index
 References
 Isbn
 9783319750019
 Label
 ErrorsinVariables Methods in System Identification
 Title
 ErrorsinVariables Methods in System Identification
 Statement of responsibility
 by Torsten Söderström
 Language
 eng
 Summary
 This book presents an overview of the different errorsinvariables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a nontrivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuoustime models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on biascompensation; covariance matching methods; and prediction error and maximumlikelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. ErrorsinVariables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving overdetermined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.
 http://library.link/vocab/creatorName
 Söderström, Torsten
 http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
 GHQ3w71835I
 Image bit depth
 0
 LC call number
 TJ212225
 Literary form
 non fiction
 Series statement
 Communications and Control Engineering,
 http://library.link/vocab/subjectName

 Automatic control
 System theory
 Electrical engineering
 Computer networks
 Statistics
 Control and Systems Theory
 Systems Theory, Control
 Communications Engineering, Networks
 Computer Communication Networks
 Statistical Theory and Methods
 Label
 ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Chapter 1. Introduction  Chapter 2. The Static Case  Chapter 3. The ErrorsinVariables Problem for Dynamic Systems  Chapter 4. Identifiability Aspects  Chapter 5. Modeling Aspects  Chapter 6. Elementary Methods  Chapter 7. Methods Based on BiasCompensation  Chapter 8. Covariance Matching  Chapter 9. Prediction Error and Maximum Likelihood Methods  Chapter 10. Frequency Domain Methods  Chapter 11. Total Least Squares  Chapter 12. Methods for Periodic Data  Chapter 13. Algorithmic Properties  Chapter 14. Asymptotic Distributions  Chapter 15. ErrorsinVariables Problems in Practice  Index  References
 Dimensions
 unknown
 Edition
 1st ed. 2018.
 Extent
 XXVII, 485 p. 30 illus., 3 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783319750019
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9783319750019
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783319750019
 Label
 ErrorsinVariables Methods in System Identification, by Torsten Söderström, (electronic resource)
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Chapter 1. Introduction  Chapter 2. The Static Case  Chapter 3. The ErrorsinVariables Problem for Dynamic Systems  Chapter 4. Identifiability Aspects  Chapter 5. Modeling Aspects  Chapter 6. Elementary Methods  Chapter 7. Methods Based on BiasCompensation  Chapter 8. Covariance Matching  Chapter 9. Prediction Error and Maximum Likelihood Methods  Chapter 10. Frequency Domain Methods  Chapter 11. Total Least Squares  Chapter 12. Methods for Periodic Data  Chapter 13. Algorithmic Properties  Chapter 14. Asymptotic Distributions  Chapter 15. ErrorsinVariables Problems in Practice  Index  References
 Dimensions
 unknown
 Edition
 1st ed. 2018.
 Extent
 XXVII, 485 p. 30 illus., 3 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9783319750019
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other control number
 10.1007/9783319750019
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
 System control number
 (DEHe213)9783319750019
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