Myriad-Type Polynomial Filtering
Linear combinations of polynomial terms yield poor performance in environments characterized by heavy-tailed distributions. Weighted myriad (WMy) filters, however, are well known for their outlier suppression and detail preservation properties. It is shown here that the WMy methodology is naturally...
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| Veröffentlicht in: | IEEE transactions on signal processing 2007-02, Vol.55 (2), p.747-753 |
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| container_title | IEEE transactions on signal processing |
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| creator | Aysal, T.C. Barner, K.E. |
| description | Linear combinations of polynomial terms yield poor performance in environments characterized by heavy-tailed distributions. Weighted myriad (WMy) filters, however, are well known for their outlier suppression and detail preservation properties. It is shown here that the WMy methodology is naturally extended to the polynomial sample case, yielding filter structures that exploit the higher order statistics of the observed samples while simultaneously being robust to outliers for heavy-tailed distributions environments. Moreover, the introduced power weighted myriad (PWMy) filter class is well motivated by analysis of cross- and square-term statistics of heavy-tailed distributions. The effectiveness of the proposed filter is evaluated through simulations |
| doi_str_mv | 10.1109/TSP.2006.885758 |
| format | Article |
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Weighted myriad (WMy) filters, however, are well known for their outlier suppression and detail preservation properties. It is shown here that the WMy methodology is naturally extended to the polynomial sample case, yielding filter structures that exploit the higher order statistics of the observed samples while simultaneously being robust to outliers for heavy-tailed distributions environments. Moreover, the introduced power weighted myriad (PWMy) filter class is well motivated by analysis of cross- and square-term statistics of heavy-tailed distributions. The effectiveness of the proposed filter is evaluated through simulations</description><identifier>ISSN: 1053-587X</identifier><identifier>EISSN: 1941-0476</identifier><identifier>DOI: 10.1109/TSP.2006.885758</identifier><identifier>CODEN: ITPRED</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>alpha -stable distributions ; Applied sciences ; Detection, estimation, filtering, equalization, prediction ; Exact sciences and technology ; Filtering ; Filters ; Filtration ; Higher order statistics ; impulsive processes ; Information, signal and communications theory ; Laplace equations ; myriad filters ; Nonlinear systems ; polynomial filtering ; Polynomials ; Pulse width modulation ; Robustness ; Samples ; Signal and communications theory ; Signal processing ; Signal, noise ; Simulation ; Statistical analysis ; Statistical distributions ; Statistical methods ; Statistics ; Telecommunications and information theory ; Volterra series</subject><ispartof>IEEE transactions on signal processing, 2007-02, Vol.55 (2), p.747-753</ispartof><rights>2007 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Weighted myriad (WMy) filters, however, are well known for their outlier suppression and detail preservation properties. It is shown here that the WMy methodology is naturally extended to the polynomial sample case, yielding filter structures that exploit the higher order statistics of the observed samples while simultaneously being robust to outliers for heavy-tailed distributions environments. Moreover, the introduced power weighted myriad (PWMy) filter class is well motivated by analysis of cross- and square-term statistics of heavy-tailed distributions. The effectiveness of the proposed filter is evaluated through simulations</description><subject>alpha -stable distributions</subject><subject>Applied sciences</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>Filtering</subject><subject>Filters</subject><subject>Filtration</subject><subject>Higher order statistics</subject><subject>impulsive processes</subject><subject>Information, signal and communications theory</subject><subject>Laplace equations</subject><subject>myriad filters</subject><subject>Nonlinear systems</subject><subject>polynomial filtering</subject><subject>Polynomials</subject><subject>Pulse width modulation</subject><subject>Robustness</subject><subject>Samples</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal, noise</subject><subject>Simulation</subject><subject>Statistical analysis</subject><subject>Statistical distributions</subject><subject>Statistical methods</subject><subject>Statistics</subject><subject>Telecommunications and information theory</subject><subject>Volterra series</subject><issn>1053-587X</issn><issn>1941-0476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kE1LAzEQhoMoqNWzBy9FUE_bJjv5mBylWBUqFqzgLcRtIinb3Zq0h_337rJFwYOnGZhn3mEeQi4YHTFG9XjxOh_llMoRolACD8gJ05xllCt52PZUQCZQvR-T05RWlDLOtTwhw-cmBrvMFs3GDed12VT1OthyOA3l1sVQfZ6RI2_L5M73dUDepveLyWM2e3l4mtzNsgKQbbMPRyWzCCrHJfeSArils8xaUNx7T61HLBAly5UHpkGD1LxwTjCqNDgKA3Lb525i_bVzaWvWIRWuLG3l6l0yiBoUSiVb8uZfEjhqwSFvwas_4Krexar9wqDkApRU3d1xDxWxTik6bzYxrG1sDKOmE2tasaYTa3qx7cb1PtamwpY-2qoI6XcNW7NcdsmXPReccz9jTiUIYPANKZZ-KA</recordid><startdate>20070201</startdate><enddate>20070201</enddate><creator>Aysal, T.C.</creator><creator>Barner, K.E.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20070201</creationdate><title>Myriad-Type Polynomial Filtering</title><author>Aysal, T.C. ; Barner, K.E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c381t-be061a83728d4f6033edea1aa374fff0af88c886127f319393694cee510793e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>alpha -stable distributions</topic><topic>Applied sciences</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Exact sciences and technology</topic><topic>Filtering</topic><topic>Filters</topic><topic>Filtration</topic><topic>Higher order statistics</topic><topic>impulsive processes</topic><topic>Information, signal and communications theory</topic><topic>Laplace equations</topic><topic>myriad filters</topic><topic>Nonlinear systems</topic><topic>polynomial filtering</topic><topic>Polynomials</topic><topic>Pulse width modulation</topic><topic>Robustness</topic><topic>Samples</topic><topic>Signal and communications theory</topic><topic>Signal processing</topic><topic>Signal, noise</topic><topic>Simulation</topic><topic>Statistical analysis</topic><topic>Statistical distributions</topic><topic>Statistical methods</topic><topic>Statistics</topic><topic>Telecommunications and information theory</topic><topic>Volterra series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Aysal, T.C.</creatorcontrib><creatorcontrib>Barner, K.E.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Aysal, T.C.</au><au>Barner, K.E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Myriad-Type Polynomial Filtering</atitle><jtitle>IEEE transactions on signal processing</jtitle><stitle>TSP</stitle><date>2007-02-01</date><risdate>2007</risdate><volume>55</volume><issue>2</issue><spage>747</spage><epage>753</epage><pages>747-753</pages><issn>1053-587X</issn><eissn>1941-0476</eissn><coden>ITPRED</coden><abstract>Linear combinations of polynomial terms yield poor performance in environments characterized by heavy-tailed distributions. Weighted myriad (WMy) filters, however, are well known for their outlier suppression and detail preservation properties. It is shown here that the WMy methodology is naturally extended to the polynomial sample case, yielding filter structures that exploit the higher order statistics of the observed samples while simultaneously being robust to outliers for heavy-tailed distributions environments. Moreover, the introduced power weighted myriad (PWMy) filter class is well motivated by analysis of cross- and square-term statistics of heavy-tailed distributions. The effectiveness of the proposed filter is evaluated through simulations</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TSP.2006.885758</doi><tpages>7</tpages></addata></record> |
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| ispartof | IEEE transactions on signal processing, 2007-02, Vol.55 (2), p.747-753 |
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| source | IEEE Electronic Library (IEL) |
| subjects | alpha -stable distributions Applied sciences Detection, estimation, filtering, equalization, prediction Exact sciences and technology Filtering Filters Filtration Higher order statistics impulsive processes Information, signal and communications theory Laplace equations myriad filters Nonlinear systems polynomial filtering Polynomials Pulse width modulation Robustness Samples Signal and communications theory Signal processing Signal, noise Simulation Statistical analysis Statistical distributions Statistical methods Statistics Telecommunications and information theory Volterra series |
| title | Myriad-Type Polynomial Filtering |
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