Recoverability analysis of block-sparse representation
Recoverability of block-sparse signals by convex relaxation methods is considered for the underdetermined linear model. In previous works, some explicit but pessimistic recoverability results which were associated with the dictionary were presented. This paper shows the recoverability of block-spars...
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| Veröffentlicht in: | Journal of systems engineering and electronics 2014-06, Vol.25 (3), p.373-379 |
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| container_title | Journal of systems engineering and electronics |
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| creator | Fu, Yuli Zou, Jian Zhang, Qiheng Li, Haifeng |
| description | Recoverability of block-sparse signals by convex relaxation methods is considered for the underdetermined linear model. In previous works, some explicit but pessimistic recoverability results which were associated with the dictionary were presented. This paper shows the recoverability of block-sparse signals are associated with the block structure when a random dictionary is given. Several probability inequalities are obtained to show how the recoverability changes along with the block structure parameters, such as the number of nonzero blocks, the block length, the dimension of the measurements and the dimension of the block-sparse representation signal. Also, this paper concludes that if the block-sparse structure can be considered, the recoverability of the signals wil be improved. Numerical examples are given to il ustrate the availability of the presented theoretical results. |
| doi_str_mv | 10.1109/JSEE.2014.00042 |
| format | Article |
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In previous works, some explicit but pessimistic recoverability results which were associated with the dictionary were presented. This paper shows the recoverability of block-sparse signals are associated with the block structure when a random dictionary is given. Several probability inequalities are obtained to show how the recoverability changes along with the block structure parameters, such as the number of nonzero blocks, the block length, the dimension of the measurements and the dimension of the block-sparse representation signal. Also, this paper concludes that if the block-sparse structure can be considered, the recoverability of the signals wil be improved. 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All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c411t-c605985df72077f42546598929883e3a7cf22028ee725bd67ee3371ab6247da3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://image.cqvip.com/vip1000/qk/85918X/85918X.jpg</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Fu, Yuli</creatorcontrib><creatorcontrib>Zou, Jian</creatorcontrib><creatorcontrib>Zhang, Qiheng</creatorcontrib><creatorcontrib>Li, Haifeng</creatorcontrib><title>Recoverability analysis of block-sparse representation</title><title>Journal of systems engineering and electronics</title><addtitle>Journal of Systems Engineering and Electronics</addtitle><description>Recoverability of block-sparse signals by convex relaxation methods is considered for the underdetermined linear model. In previous works, some explicit but pessimistic recoverability results which were associated with the dictionary were presented. This paper shows the recoverability of block-sparse signals are associated with the block structure when a random dictionary is given. Several probability inequalities are obtained to show how the recoverability changes along with the block structure parameters, such as the number of nonzero blocks, the block length, the dimension of the measurements and the dimension of the block-sparse representation signal. Also, this paper concludes that if the block-sparse structure can be considered, the recoverability of the signals wil be improved. Numerical examples are given to il ustrate the availability of the presented theoretical results.</description><subject>Availability</subject><subject>Blocking</subject><subject>Dictionaries</subject><subject>Dimensional measurements</subject><subject>Inequalities</subject><subject>Mathematical models</subject><subject>Recoverability</subject><subject>Representations</subject><subject>信号</subject><subject>可恢复性</subject><subject>松弛法</subject><subject>概率不等式</subject><subject>稀疏表示</subject><subject>线性模型</subject><subject>结构参数</subject><subject>结构相关</subject><issn>1004-4132</issn><issn>1004-4132</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFkM1PwzAMxSMEEhPszLXcONDNSZqmPaJpfGkSEuwepa07OrqmSzqg_PWkbEjc8MWW9XvW8yPkgsKEUkinjy_z-YQBjSYAELEjMqK-hxHl7PjPfErGzq1hKAmMwYjEz5ibd7Q6q-qq6wPd6Lp3lQtMGWS1yd9C12rrMLDYWnTYdLqrTHNOTkpdOxwf-hlZ3s6Xs_tw8XT3MLtZhHlEaRfmMYg0EUUpGUhZRkxEsV-kLE0SjlzLvPQuWIIomciKWCJyLqnOYhbJQvMzcr0_-6GbUjcrtTY76x069dmt8r74WjuFw9vAAZjHr_Z4a812h65Tm8rlWNe6QbNzisYyAQrC4_-iIpY-ozROPDrdo7k1zlksVWurjba9oqCG9NWQvhpsqJ_0veLyoHg1zWpbeeO_EgEsFYJL_g1IbYBt</recordid><startdate>20140601</startdate><enddate>20140601</enddate><creator>Fu, Yuli</creator><creator>Zou, Jian</creator><creator>Zhang, Qiheng</creator><creator>Li, Haifeng</creator><general>School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20140601</creationdate><title>Recoverability analysis of block-sparse representation</title><author>Fu, Yuli ; Zou, Jian ; Zhang, Qiheng ; Li, Haifeng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c411t-c605985df72077f42546598929883e3a7cf22028ee725bd67ee3371ab6247da3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Availability</topic><topic>Blocking</topic><topic>Dictionaries</topic><topic>Dimensional measurements</topic><topic>Inequalities</topic><topic>Mathematical models</topic><topic>Recoverability</topic><topic>Representations</topic><topic>信号</topic><topic>可恢复性</topic><topic>松弛法</topic><topic>概率不等式</topic><topic>稀疏表示</topic><topic>线性模型</topic><topic>结构参数</topic><topic>结构相关</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Fu, Yuli</creatorcontrib><creatorcontrib>Zou, Jian</creatorcontrib><creatorcontrib>Zhang, Qiheng</creatorcontrib><creatorcontrib>Li, Haifeng</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Journal of systems engineering and electronics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Fu, Yuli</au><au>Zou, Jian</au><au>Zhang, Qiheng</au><au>Li, Haifeng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Recoverability analysis of block-sparse representation</atitle><jtitle>Journal of systems engineering and electronics</jtitle><addtitle>Journal of Systems Engineering and Electronics</addtitle><date>2014-06-01</date><risdate>2014</risdate><volume>25</volume><issue>3</issue><spage>373</spage><epage>379</epage><pages>373-379</pages><issn>1004-4132</issn><eissn>1004-4132</eissn><abstract>Recoverability of block-sparse signals by convex relaxation methods is considered for the underdetermined linear model. In previous works, some explicit but pessimistic recoverability results which were associated with the dictionary were presented. This paper shows the recoverability of block-sparse signals are associated with the block structure when a random dictionary is given. Several probability inequalities are obtained to show how the recoverability changes along with the block structure parameters, such as the number of nonzero blocks, the block length, the dimension of the measurements and the dimension of the block-sparse representation signal. Also, this paper concludes that if the block-sparse structure can be considered, the recoverability of the signals wil be improved. Numerical examples are given to il ustrate the availability of the presented theoretical results.</abstract><pub>School of Electronic and Information Engineering, South China University of Technology, Guangzhou 510640, China</pub><doi>10.1109/JSEE.2014.00042</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| language | eng |
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| source | IEEE Power & Energy Library; EZB-FREE-00999 freely available EZB journals |
| subjects | Availability Blocking Dictionaries Dimensional measurements Inequalities Mathematical models Recoverability Representations 信号 可恢复性 松弛法 概率不等式 稀疏表示 线性模型 结构参数 结构相关 |
| title | Recoverability analysis of block-sparse representation |
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