View in EDS HTML Full Text PDF Full Text

Recursive Generalized Maximum Correntropy Criterion Algorithm with Sparse Penalty Constraints for System Identification.

Saved in:
Bibliographic Details
Title: Recursive Generalized Maximum Correntropy Criterion Algorithm with Sparse Penalty Constraints for System Identification.
Authors: Ma, Wentao1 xjtu.wentaoma@gmail.com, Duan, Jiandong1, Chen, Badong2, Gui, Guan3, Man, Weishi1
Source: Asian Journal of Control. May2017, Vol. 19 Issue 3, p1164-1172. 9p.
Subjects: System identification, Recursive programming, Computer simulation, Estimation theory, System analysis
Abstract: To address the sparse system identification problem in a non-Gaussian impulsive noise environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm with sparse penalty constraints is proposed to combat impulsive-inducing instability. Specifically, a recursive algorithm based on the generalized correntropy with a forgetting factor of error is developed to improve the performance of the sparsity aware maximum correntropy criterion algorithms by achieving a robust steady-state error. Considering an unknown sparse system, the l 1-norm and correntropy induced metric are employed in the RGMCC algorithm to exploit sparsity as well as to mitigate impulsive noise simultaneously. Numerical simulations are given to show that the proposed algorithm is robust while providing robust steady-state estimation performance. [ABSTRACT FROM AUTHOR]
Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 122917970
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Recursive Generalized Maximum Correntropy Criterion Algorithm with Sparse Penalty Constraints for System Identification.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ma%2C+Wentao%22">Ma, Wentao</searchLink><relatesTo>1</relatesTo><i> xjtu.wentaoma@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Duan%2C+Jiandong%22">Duan, Jiandong</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Badong%22">Chen, Badong</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Gui%2C+Guan%22">Gui, Guan</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Man%2C+Weishi%22">Man, Weishi</searchLink><relatesTo>1</relatesTo>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Asian+Journal+of+Control%22">Asian Journal of Control</searchLink>. May2017, Vol. 19 Issue 3, p1164-1172. 9p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22System+identification%22">System identification</searchLink><br /><searchLink fieldCode="DE" term="%22Recursive+programming%22">Recursive programming</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br /><searchLink fieldCode="DE" term="%22Estimation+theory%22">Estimation theory</searchLink><br /><searchLink fieldCode="DE" term="%22System+analysis%22">System analysis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To address the sparse system identification problem in a non-Gaussian impulsive noise environment, the recursive generalized maximum correntropy criterion (RGMCC) algorithm with sparse penalty constraints is proposed to combat impulsive-inducing instability. Specifically, a recursive algorithm based on the generalized correntropy with a forgetting factor of error is developed to improve the performance of the sparsity aware maximum correntropy criterion algorithms by achieving a robust steady-state error. Considering an unknown sparse system, the l 1-norm and correntropy induced metric are employed in the RGMCC algorithm to exploit sparsity as well as to mitigate impulsive noise simultaneously. Numerical simulations are given to show that the proposed algorithm is robust while providing robust steady-state estimation performance. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Asian Journal of Control is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=122917970
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1002/asjc.1448
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 1164
    Subjects:
      – SubjectFull: System identification
        Type: general
      – SubjectFull: Recursive programming
        Type: general
      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Estimation theory
        Type: general
      – SubjectFull: System analysis
        Type: general
    Titles:
      – TitleFull: Recursive Generalized Maximum Correntropy Criterion Algorithm with Sparse Penalty Constraints for System Identification.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ma, Wentao
      – PersonEntity:
          Name:
            NameFull: Duan, Jiandong
      – PersonEntity:
          Name:
            NameFull: Chen, Badong
      – PersonEntity:
          Name:
            NameFull: Gui, Guan
      – PersonEntity:
          Name:
            NameFull: Man, Weishi
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2017
              Type: published
              Y: 2017
          Identifiers:
            – Type: issn-print
              Value: 15618625
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: Asian Journal of Control
              Type: main
ResultId 1