Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments
A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diff...
Gespeichert in:
| Veröffentlicht in: | Electronics letters 2013-10, Vol.49 (21), p.1355-1356 |
|---|---|
| 1. Verfasser: | |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 1356 |
|---|---|
| container_issue | 21 |
| container_start_page | 1355 |
| container_title | Electronics letters |
| container_volume | 49 |
| creator | Wen, F |
| description | A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diffusion LMP methods when the noise is with alpha-stable distribution. |
| doi_str_mv | 10.1049/el.2013.2331 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_24P</sourceid><recordid>TN_cdi_proquest_journals_1466276764</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1671449384</sourcerecordid><originalsourceid>FETCH-LOGICAL-c5385-aeef822954145dd53f9fa0d65c921698b6019e3cbb73fb364a9f9cbec8aaad123</originalsourceid><addsrcrecordid>eNp9kE1r1UAUhoMoeKnd-QMCKrhorvOdzFLrrRYCulBwN0wmZ-zIZCbOJJb--064RYuUrg4cnvPynLeqXmK0x4jJd-D3BGG6J5TiJ9UOU44aifGPp9UOlX3DsWTPq9Oc3YAww0wghncVfHTWrtnFUHvQeWkm0KH-2szxGlKt_c-Y3HI15drGVI8uL8kN6wJjDXlxk162QxcKOF_pJi968FCH6DLUEP64FMMEYckvqmdW-wynd_Ok-n5x-Hb-uem_fLo8f983htOONxrAdoRIXvT4OHJqpdVoFNxIgoXsBoGwBGqGoaV2oIJpaaUZwHRa6xETelK9PebOKf5ei6KaXDbgvQ4Q16ywaDFjknasoK_-Q3_FNYVip0o3grSiFRt1dqRMijknsGpO5e10ozBSW-0KvNpqV1vtBX9zF6qz0d4mHYzLf29I28quQxvHj9y183DzaKY69D35cIFQR_m__xzc931Y5fUD6KG_lzyPlt4CDf6rtA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1466276764</pqid></control><display><type>article</type><title>Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments</title><source>Wiley Online Library Open Access</source><creator>Wen, F</creator><creatorcontrib>Wen, F</creatorcontrib><description>A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diffusion LMP methods when the noise is with alpha-stable distribution.</description><identifier>ISSN: 0013-5194</identifier><identifier>ISSN: 1350-911X</identifier><identifier>EISSN: 1350-911X</identifier><identifier>DOI: 10.1049/el.2013.2331</identifier><identifier>CODEN: ELLEAK</identifier><language>eng</language><publisher>Stevenage: The Institution of Engineering and Technology</publisher><subject>adaptive estimation ; Algorithms ; alpha‐stable distribution ; alpha‐stable noise environment ; Applied sciences ; Detection, estimation, filtering, equalization, prediction ; Diffusion ; diffusion least‐mean P‐power algorithm ; distributed estimation ; Exact sciences and technology ; impulse noise ; Information, signal and communications theory ; least mean squares methods ; least‐mean square algorithm ; LMP algorithm ; Noise ; Signal and communications theory ; signal processing ; Signal, noise ; Telecommunications and information theory ; Wireless communications</subject><ispartof>Electronics letters, 2013-10, Vol.49 (21), p.1355-1356</ispartof><rights>The Institution of Engineering and Technology</rights><rights>2020 The Institution of Engineering and Technology</rights><rights>2014 INIST-CNRS</rights><rights>Copyright The Institution of Engineering & Technology Oct 10, 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5385-aeef822954145dd53f9fa0d65c921698b6019e3cbb73fb364a9f9cbec8aaad123</citedby><cites>FETCH-LOGICAL-c5385-aeef822954145dd53f9fa0d65c921698b6019e3cbb73fb364a9f9cbec8aaad123</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1049%2Fel.2013.2331$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1049%2Fel.2013.2331$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,11542,27903,27904,45553,45554,46031,46455</link.rule.ids><linktorsrc>$$Uhttps://onlinelibrary.wiley.com/doi/abs/10.1049%2Fel.2013.2331$$EView_record_in_Wiley-Blackwell$$FView_record_in_$$GWiley-Blackwell</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27798801$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Wen, F</creatorcontrib><title>Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments</title><title>Electronics letters</title><description>A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diffusion LMP methods when the noise is with alpha-stable distribution.</description><subject>adaptive estimation</subject><subject>Algorithms</subject><subject>alpha‐stable distribution</subject><subject>alpha‐stable noise environment</subject><subject>Applied sciences</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Diffusion</subject><subject>diffusion least‐mean P‐power algorithm</subject><subject>distributed estimation</subject><subject>Exact sciences and technology</subject><subject>impulse noise</subject><subject>Information, signal and communications theory</subject><subject>least mean squares methods</subject><subject>least‐mean square algorithm</subject><subject>LMP algorithm</subject><subject>Noise</subject><subject>Signal and communications theory</subject><subject>signal processing</subject><subject>Signal, noise</subject><subject>Telecommunications and information theory</subject><subject>Wireless communications</subject><issn>0013-5194</issn><issn>1350-911X</issn><issn>1350-911X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kE1r1UAUhoMoeKnd-QMCKrhorvOdzFLrrRYCulBwN0wmZ-zIZCbOJJb--064RYuUrg4cnvPynLeqXmK0x4jJd-D3BGG6J5TiJ9UOU44aifGPp9UOlX3DsWTPq9Oc3YAww0wghncVfHTWrtnFUHvQeWkm0KH-2szxGlKt_c-Y3HI15drGVI8uL8kN6wJjDXlxk162QxcKOF_pJi968FCH6DLUEP64FMMEYckvqmdW-wynd_Ok-n5x-Hb-uem_fLo8f983htOONxrAdoRIXvT4OHJqpdVoFNxIgoXsBoGwBGqGoaV2oIJpaaUZwHRa6xETelK9PebOKf5ei6KaXDbgvQ4Q16ywaDFjknasoK_-Q3_FNYVip0o3grSiFRt1dqRMijknsGpO5e10ozBSW-0KvNpqV1vtBX9zF6qz0d4mHYzLf29I28quQxvHj9y183DzaKY69D35cIFQR_m__xzc931Y5fUD6KG_lzyPlt4CDf6rtA</recordid><startdate>20131010</startdate><enddate>20131010</enddate><creator>Wen, F</creator><general>The Institution of Engineering and Technology</general><general>Institution of Engineering and Technology</general><general>John Wiley & Sons, Inc</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>7SP</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20131010</creationdate><title>Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments</title><author>Wen, F</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5385-aeef822954145dd53f9fa0d65c921698b6019e3cbb73fb364a9f9cbec8aaad123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>adaptive estimation</topic><topic>Algorithms</topic><topic>alpha‐stable distribution</topic><topic>alpha‐stable noise environment</topic><topic>Applied sciences</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Diffusion</topic><topic>diffusion least‐mean P‐power algorithm</topic><topic>distributed estimation</topic><topic>Exact sciences and technology</topic><topic>impulse noise</topic><topic>Information, signal and communications theory</topic><topic>least mean squares methods</topic><topic>least‐mean square algorithm</topic><topic>LMP algorithm</topic><topic>Noise</topic><topic>Signal and communications theory</topic><topic>signal processing</topic><topic>Signal, noise</topic><topic>Telecommunications and information theory</topic><topic>Wireless communications</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wen, F</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Electronics letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wen, F</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments</atitle><jtitle>Electronics letters</jtitle><date>2013-10-10</date><risdate>2013</risdate><volume>49</volume><issue>21</issue><spage>1355</spage><epage>1356</epage><pages>1355-1356</pages><issn>0013-5194</issn><issn>1350-911X</issn><eissn>1350-911X</eissn><coden>ELLEAK</coden><abstract>A diffusion least-mean P-power (LMP) algorithm is proposed for distributed estimation in alpha-stable noise environments, which is one of the widely used models that appears in various environments. Compared with the diffusion least-mean squares algorithm, better performance is obtained for the diffusion LMP methods when the noise is with alpha-stable distribution.</abstract><cop>Stevenage</cop><pub>The Institution of Engineering and Technology</pub><doi>10.1049/el.2013.2331</doi><tpages>2</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 0013-5194 |
| ispartof | Electronics letters, 2013-10, Vol.49 (21), p.1355-1356 |
| issn | 0013-5194 1350-911X 1350-911X |
| language | eng |
| recordid | cdi_proquest_journals_1466276764 |
| source | Wiley Online Library Open Access |
| subjects | adaptive estimation Algorithms alpha‐stable distribution alpha‐stable noise environment Applied sciences Detection, estimation, filtering, equalization, prediction Diffusion diffusion least‐mean P‐power algorithm distributed estimation Exact sciences and technology impulse noise Information, signal and communications theory least mean squares methods least‐mean square algorithm LMP algorithm Noise Signal and communications theory signal processing Signal, noise Telecommunications and information theory Wireless communications |
| title | Diffusion least-mean P-power algorithms for distributed estimation in alpha-stable noise environments |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T14%3A42%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_24P&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Diffusion%20least-mean%20P-power%20algorithms%20for%20distributed%20estimation%20in%20alpha-stable%20noise%20environments&rft.jtitle=Electronics%20letters&rft.au=Wen,%20F&rft.date=2013-10-10&rft.volume=49&rft.issue=21&rft.spage=1355&rft.epage=1356&rft.pages=1355-1356&rft.issn=0013-5194&rft.eissn=1350-911X&rft.coden=ELLEAK&rft_id=info:doi/10.1049/el.2013.2331&rft_dat=%3Cproquest_24P%3E1671449384%3C/proquest_24P%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1466276764&rft_id=info:pmid/&rfr_iscdi=true |