Non-Linear Transform-Based Robust Adaptive Latency Change Estimation of Evoked Potentials
Objectives: To improve the latency change estimation of evoked potentials (EP) under the lower order α-stable noise conditions by proposing and analyzing a new adaptive EP latency change detection algorithm (referred to as the NLST). Methods: The NLST algorithm is based on the fractional lower order...
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| Veröffentlicht in: | Methods of information in medicine 2002-01, Vol.41 (4), p.331-336 |
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| creator | Qiu, T. Wang, H. Zhang, Y. Bao, H. |
| description | Objectives: To improve the latency change estimation of evoked potentials (EP) under the lower order α-stable noise conditions by proposing and analyzing a new adaptive EP latency change detection algorithm (referred to as the NLST). Methods: The NLST algorithm is based on the fractional lower order moment and the nonlinear transform for the error function. The computer simulation and data analysis verify the robustness of the new algorithm. Results: The theoretical analysis shows that the iteration equation of the NLST transforms the lower order α-stable process e n (k) into a second order moment process by a nonlinear transform. The simulations and the data analysis showed the robustness of the NLST under the lower order -stable noise conditions. Conclusions: The new algorithm is robust under the lower order α-stable noise conditions, and it also provides a better performance than the DLMS, DLMP and SDA algorithms without the need to estimate the value of the EP signals and noises. |
| doi_str_mv | 10.1055/s-0038-1634390 |
| format | Article |
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Methods: The NLST algorithm is based on the fractional lower order moment and the nonlinear transform for the error function. The computer simulation and data analysis verify the robustness of the new algorithm. Results: The theoretical analysis shows that the iteration equation of the NLST transforms the lower order α-stable process e n (k) into a second order moment process by a nonlinear transform. The simulations and the data analysis showed the robustness of the NLST under the lower order -stable noise conditions. Conclusions: The new algorithm is robust under the lower order α-stable noise conditions, and it also provides a better performance than the DLMS, DLMP and SDA algorithms without the need to estimate the value of the EP signals and noises.</description><identifier>ISSN: 0026-1270</identifier><identifier>EISSN: 2511-705X</identifier><identifier>DOI: 10.1055/s-0038-1634390</identifier><identifier>PMID: 12425245</identifier><identifier>CODEN: MIMCAI</identifier><language>eng</language><publisher>Stuttgart: Schattauer Verlag für Medizin und Naturwissenschaften</publisher><subject>adaptive ; Algorithms ; Biological and medical sciences ; Central Nervous System - injuries ; Electrodiagnosis. Electric activity recording ; Evoked Potentials ; Evoked Potentials, Somatosensory - physiology ; Humans ; Hypoxia, Brain - physiopathology ; Investigative techniques, diagnostic techniques (general aspects) ; latency ; Medical sciences ; Nervous system ; nonlinear ; Nonlinear Dynamics ; Original article ; Reaction Time - physiology ; signal detection ; Signal Processing, Computer-Assisted</subject><ispartof>Methods of information in medicine, 2002-01, Vol.41 (4), p.331-336</ispartof><rights>2002 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c661t-9db06bef8df8626f64aabafdf45d729d536dc2fc979378f70db0871909cc24b3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.thieme-connect.de/products/ejournals/pdf/10.1055/s-0038-1634390.pdf$$EPDF$$P50$$Gthieme$$H</linktopdf><linktohtml>$$Uhttps://www.thieme-connect.de/products/ejournals/html/10.1055/s-0038-1634390$$EHTML$$P50$$Gthieme$$H</linktohtml><link.rule.ids>315,781,785,3018,3019,27929,27930,54564,54565</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=13965322$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12425245$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Qiu, T.</creatorcontrib><creatorcontrib>Wang, H.</creatorcontrib><creatorcontrib>Zhang, Y.</creatorcontrib><creatorcontrib>Bao, H.</creatorcontrib><title>Non-Linear Transform-Based Robust Adaptive Latency Change Estimation of Evoked Potentials</title><title>Methods of information in medicine</title><addtitle>Methods Inf Med</addtitle><description>Objectives: To improve the latency change estimation of evoked potentials (EP) under the lower order α-stable noise conditions by proposing and analyzing a new adaptive EP latency change detection algorithm (referred to as the NLST). Methods: The NLST algorithm is based on the fractional lower order moment and the nonlinear transform for the error function. The computer simulation and data analysis verify the robustness of the new algorithm. Results: The theoretical analysis shows that the iteration equation of the NLST transforms the lower order α-stable process e n (k) into a second order moment process by a nonlinear transform. The simulations and the data analysis showed the robustness of the NLST under the lower order -stable noise conditions. Conclusions: The new algorithm is robust under the lower order α-stable noise conditions, and it also provides a better performance than the DLMS, DLMP and SDA algorithms without the need to estimate the value of the EP signals and noises.</description><subject>adaptive</subject><subject>Algorithms</subject><subject>Biological and medical sciences</subject><subject>Central Nervous System - injuries</subject><subject>Electrodiagnosis. Electric activity recording</subject><subject>Evoked Potentials</subject><subject>Evoked Potentials, Somatosensory - physiology</subject><subject>Humans</subject><subject>Hypoxia, Brain - physiopathology</subject><subject>Investigative techniques, diagnostic techniques (general aspects)</subject><subject>latency</subject><subject>Medical sciences</subject><subject>Nervous system</subject><subject>nonlinear</subject><subject>Nonlinear Dynamics</subject><subject>Original article</subject><subject>Reaction Time - physiology</subject><subject>signal detection</subject><subject>Signal Processing, Computer-Assisted</subject><issn>0026-1270</issn><issn>2511-705X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNrFkU9v1DAQxSMEokvhyhHlQm8ptpM4ybGslj_SChDaA5xGjjNuXDZx8DhddT8LBz4qXu2KcukZydIc_Js3T-8lyUvOLjkryzeUMZbXGZd5kTfsUbIQJedZxcpvj5MFY0JmXFTsLHlGdMMYq2tWPE3OuChEKYpykXz_5MZsbUdUPt14NZJxfsjeKsIu_eramUJ61akp2FtM1yrgqO_SZa_Ga0xXFOyggnVj6ky6unU_4s4XF5lg1ZaeJ09MHPjiNM-TzbvVZvkhW39-_3F5tc60lDxkTdcy2aKpO1NLIY0slGqV6UxRdpVoujKXnRZGN1WTV7WpWOTrijes0VoUbX6eXBxlJ-9-zkgBBksat1s1opsJKiFlE4UjeHkEtXdEHg1MPvr3d8AZHLIEgkOWcMoyLrw6Kc_tgN09fgovAq9PgCKttibGpy3dc3kjy1yIyGVHLvQWB4QbN_sxRvLw4d9HnnSvQlAz-r-ifQgT7HY7-Oevw8Mb1LXaxyJhxhY9Wd0H2KMNEfTWxFZAwR4GDL3rCLQbD0URKK_7WO7kcbDzAJZoRqAJdewwao4zaW-nACIvgHq3iw6GbbT46z9brBh_2N4fCOgLPQ</recordid><startdate>20020101</startdate><enddate>20020101</enddate><creator>Qiu, T.</creator><creator>Wang, H.</creator><creator>Zhang, Y.</creator><creator>Bao, H.</creator><general>Schattauer Verlag für Medizin und Naturwissenschaften</general><general>Schattauer GmbH</general><general>Schattauer</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20020101</creationdate><title>Non-Linear Transform-Based Robust Adaptive Latency Change Estimation of Evoked Potentials</title><author>Qiu, T. ; Wang, H. ; Zhang, Y. ; Bao, H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c661t-9db06bef8df8626f64aabafdf45d729d536dc2fc979378f70db0871909cc24b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>adaptive</topic><topic>Algorithms</topic><topic>Biological and medical sciences</topic><topic>Central Nervous System - injuries</topic><topic>Electrodiagnosis. Electric activity recording</topic><topic>Evoked Potentials</topic><topic>Evoked Potentials, Somatosensory - physiology</topic><topic>Humans</topic><topic>Hypoxia, Brain - physiopathology</topic><topic>Investigative techniques, diagnostic techniques (general aspects)</topic><topic>latency</topic><topic>Medical sciences</topic><topic>Nervous system</topic><topic>nonlinear</topic><topic>Nonlinear Dynamics</topic><topic>Original article</topic><topic>Reaction Time - physiology</topic><topic>signal detection</topic><topic>Signal Processing, Computer-Assisted</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Qiu, T.</creatorcontrib><creatorcontrib>Wang, H.</creatorcontrib><creatorcontrib>Zhang, Y.</creatorcontrib><creatorcontrib>Bao, H.</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Methods of information in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Qiu, T.</au><au>Wang, H.</au><au>Zhang, Y.</au><au>Bao, H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Non-Linear Transform-Based Robust Adaptive Latency Change Estimation of Evoked Potentials</atitle><jtitle>Methods of information in medicine</jtitle><addtitle>Methods Inf Med</addtitle><date>2002-01-01</date><risdate>2002</risdate><volume>41</volume><issue>4</issue><spage>331</spage><epage>336</epage><pages>331-336</pages><issn>0026-1270</issn><eissn>2511-705X</eissn><coden>MIMCAI</coden><abstract>Objectives: To improve the latency change estimation of evoked potentials (EP) under the lower order α-stable noise conditions by proposing and analyzing a new adaptive EP latency change detection algorithm (referred to as the NLST). Methods: The NLST algorithm is based on the fractional lower order moment and the nonlinear transform for the error function. The computer simulation and data analysis verify the robustness of the new algorithm. Results: The theoretical analysis shows that the iteration equation of the NLST transforms the lower order α-stable process e n (k) into a second order moment process by a nonlinear transform. The simulations and the data analysis showed the robustness of the NLST under the lower order -stable noise conditions. Conclusions: The new algorithm is robust under the lower order α-stable noise conditions, and it also provides a better performance than the DLMS, DLMP and SDA algorithms without the need to estimate the value of the EP signals and noises.</abstract><cop>Stuttgart</cop><pub>Schattauer Verlag für Medizin und Naturwissenschaften</pub><pmid>12425245</pmid><doi>10.1055/s-0038-1634390</doi><tpages>6</tpages></addata></record> |
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| subjects | adaptive Algorithms Biological and medical sciences Central Nervous System - injuries Electrodiagnosis. Electric activity recording Evoked Potentials Evoked Potentials, Somatosensory - physiology Humans Hypoxia, Brain - physiopathology Investigative techniques, diagnostic techniques (general aspects) latency Medical sciences Nervous system nonlinear Nonlinear Dynamics Original article Reaction Time - physiology signal detection Signal Processing, Computer-Assisted |
| title | Non-Linear Transform-Based Robust Adaptive Latency Change Estimation of Evoked Potentials |
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