An adaptive system identification method based on bispectrum
The author presents an adaptive technique for the identification of a linear system driven by white non-Gaussian noise. The system can be a non-minimum phase system. The adaptive identification technique is a least-mean-square (LMS) type algorithm. It is obtained by using the higher order correlatio...
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| Veröffentlicht in: | IEEE transactions on circuits and systems 1991-08, Vol.38 (8), p.967-969 |
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| container_end_page | 969 |
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| container_issue | 8 |
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| container_title | IEEE transactions on circuits and systems |
| container_volume | 38 |
| creator | Alshebeili, S.A. Cetin, A.E. Venetsanopoulos, A.N. |
| description | The author presents an adaptive technique for the identification of a linear system driven by white non-Gaussian noise. The system can be a non-minimum phase system. The adaptive identification technique is a least-mean-square (LMS) type algorithm. It is obtained by using the higher order correlations of the system output.< > |
| doi_str_mv | 10.1109/31.85642 |
| format | Article |
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The system can be a non-minimum phase system. The adaptive identification technique is a least-mean-square (LMS) type algorithm. It is obtained by using the higher order correlations of the system output.< ></description><subject>Adaptive systems</subject><subject>Applied sciences</subject><subject>Cepstrum</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Exact sciences and technology</subject><subject>Fourier transforms</subject><subject>Higher order statistics</subject><subject>Least squares approximation</subject><subject>Linear systems</subject><subject>Modelling and identification</subject><subject>Polynomials</subject><subject>Signal processing algorithms</subject><subject>System identification</subject><subject>White noise</subject><issn>0098-4094</issn><issn>1558-1276</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1991</creationdate><recordtype>article</recordtype><recordid>eNo9z81Lw0AQBfBFFKxV8OotBw9eUneym-wOeCmlfkDBi57DZHeCK00asqvQ_95qpKfhMT8ePCGuQS4AJN4rWNiy0sWJmEFZ2hwKU52KmZRocy1Rn4uLGD-llBatnYmHZZ-RpyGFb87iPibusuC5T6ENjlLY9VnH6WPns4Yi--yQmxAHdmn86i7FWUvbyFf_dy7eH9dvq-d88_r0slpucleYIuWmRM3sUUIDhI6MagAdGgDbUEFOkvEKjYbSO4XSGauwUkpWLSFg5dRc3E29btzFOHJbD2PoaNzXIOvf1bWC-m_1gd5OdKDoaNuO1LsQj16jssbqA7uZWGDm43eq-AEseF3P</recordid><startdate>19910801</startdate><enddate>19910801</enddate><creator>Alshebeili, S.A.</creator><creator>Cetin, A.E.</creator><creator>Venetsanopoulos, A.N.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19910801</creationdate><title>An adaptive system identification method based on bispectrum</title><author>Alshebeili, S.A. ; Cetin, A.E. ; Venetsanopoulos, A.N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c272t-7594eed901b1a9ca73b19c97118ba2ac0a7d397415dc390c783963306fa9196c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1991</creationdate><topic>Adaptive systems</topic><topic>Applied sciences</topic><topic>Cepstrum</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Exact sciences and technology</topic><topic>Fourier transforms</topic><topic>Higher order statistics</topic><topic>Least squares approximation</topic><topic>Linear systems</topic><topic>Modelling and identification</topic><topic>Polynomials</topic><topic>Signal processing algorithms</topic><topic>System identification</topic><topic>White noise</topic><toplevel>online_resources</toplevel><creatorcontrib>Alshebeili, S.A.</creatorcontrib><creatorcontrib>Cetin, A.E.</creatorcontrib><creatorcontrib>Venetsanopoulos, A.N.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><jtitle>IEEE transactions on circuits and systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Alshebeili, S.A.</au><au>Cetin, A.E.</au><au>Venetsanopoulos, A.N.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An adaptive system identification method based on bispectrum</atitle><jtitle>IEEE transactions on circuits and systems</jtitle><stitle>T-CAS</stitle><date>1991-08-01</date><risdate>1991</risdate><volume>38</volume><issue>8</issue><spage>967</spage><epage>969</epage><pages>967-969</pages><issn>0098-4094</issn><eissn>1558-1276</eissn><coden>ICSYBT</coden><abstract>The author presents an adaptive technique for the identification of a linear system driven by white non-Gaussian noise. The system can be a non-minimum phase system. The adaptive identification technique is a least-mean-square (LMS) type algorithm. It is obtained by using the higher order correlations of the system output.< ></abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/31.85642</doi><tpages>3</tpages></addata></record> |
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| ispartof | IEEE transactions on circuits and systems, 1991-08, Vol.38 (8), p.967-969 |
| issn | 0098-4094 1558-1276 |
| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive systems Applied sciences Cepstrum Computer science control theory systems Control theory. Systems Exact sciences and technology Fourier transforms Higher order statistics Least squares approximation Linear systems Modelling and identification Polynomials Signal processing algorithms System identification White noise |
| title | An adaptive system identification method based on bispectrum |
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