Application of wavelet de-noising to signal demodulation
We present the application of wavelet-based de-noising techniques to the demodulation of digital communication signals. These techniques are related to those originally devised by Donoho and Johnstone (see Biometrika, v.81, p.455, 1994, and IEEE Trans. Info. Theory, vol.41, p.613, 1995) for minimum...
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| creator | Bruce, A.G. Hong-Ye Gao Mulligan, J.J. Satorius, E.H. |
| description | We present the application of wavelet-based de-noising techniques to the demodulation of digital communication signals. These techniques are related to those originally devised by Donoho and Johnstone (see Biometrika, v.81, p.455, 1994, and IEEE Trans. Info. Theory, vol.41, p.613, 1995) for minimum L/sub 2/-risk signal reconstruction. The important minimax property of wavelet de-noising filters yields significant noise reduction while retaining the essential signal features. However, the two problems are quite different, i.e., the objective is not signal reconstruction but rather minimizing bit error rate. This generally results in different design rules for optimizing performance. We show that wavelet de-noising can be effectively used for data demodulation and we propose simple design rules for its implementation. |
| doi_str_mv | 10.1109/ACSSC.1995.540878 |
| format | Conference Proceeding |
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We show that wavelet de-noising can be effectively used for data demodulation and we propose simple design rules for its implementation.</description><subject>AWGN</subject><subject>Bit error rate</subject><subject>Demodulation</subject><subject>Noise reduction</subject><subject>Sampling methods</subject><subject>Signal reconstruction</subject><subject>Timing</subject><subject>Wavelet coefficients</subject><subject>Wavelet domain</subject><subject>Wavelet transforms</subject><issn>1058-6393</issn><issn>2576-2303</issn><isbn>9780818673702</isbn><isbn>0818673702</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>1995</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotj9tKw0AURQcvYKj5AH3KD0w8J5OZOfMYglqh4EP7XuaWMpImoYmKf--lPi3YLDYsxu4QSkQwD0273bYlGiNLWQNpumBZJbXilQBxyXKjCQhJaaGhumIZgiSuhBE3LJ_nNwBAELUyJmPUTFOfvF3SOBRjV3zaj9jHpQiRD2Oa03AolrGY02Gw_c94HMN7_yffsuvO9nPM_7liu6fHXbvmm9fnl7bZ8ER64eikD7V2EqyroHKC6uAteYHBBSc1ORkUIkb9m4GGdLTRA1htjYq-Eyt2f75NMcb9dEpHe_ran6vFN66USYE</recordid><startdate>1995</startdate><enddate>1995</enddate><creator>Bruce, A.G.</creator><creator>Hong-Ye Gao</creator><creator>Mulligan, J.J.</creator><creator>Satorius, E.H.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>1995</creationdate><title>Application of wavelet de-noising to signal demodulation</title><author>Bruce, A.G. ; Hong-Ye Gao ; Mulligan, J.J. ; Satorius, E.H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i87t-1b5cd47b50ab202b384dca8c31dbdb578b5d6111e708781987eaec00a7a96ecf3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>1995</creationdate><topic>AWGN</topic><topic>Bit error rate</topic><topic>Demodulation</topic><topic>Noise reduction</topic><topic>Sampling methods</topic><topic>Signal reconstruction</topic><topic>Timing</topic><topic>Wavelet coefficients</topic><topic>Wavelet domain</topic><topic>Wavelet transforms</topic><toplevel>online_resources</toplevel><creatorcontrib>Bruce, A.G.</creatorcontrib><creatorcontrib>Hong-Ye Gao</creatorcontrib><creatorcontrib>Mulligan, J.J.</creatorcontrib><creatorcontrib>Satorius, E.H.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bruce, A.G.</au><au>Hong-Ye Gao</au><au>Mulligan, J.J.</au><au>Satorius, E.H.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Application of wavelet de-noising to signal demodulation</atitle><btitle>Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers</btitle><stitle>ACSSC</stitle><date>1995</date><risdate>1995</risdate><volume>2</volume><spage>1142</spage><epage>1146 vol.2</epage><pages>1142-1146 vol.2</pages><issn>1058-6393</issn><eissn>2576-2303</eissn><isbn>9780818673702</isbn><isbn>0818673702</isbn><abstract>We present the application of wavelet-based de-noising techniques to the demodulation of digital communication signals. These techniques are related to those originally devised by Donoho and Johnstone (see Biometrika, v.81, p.455, 1994, and IEEE Trans. Info. Theory, vol.41, p.613, 1995) for minimum L/sub 2/-risk signal reconstruction. The important minimax property of wavelet de-noising filters yields significant noise reduction while retaining the essential signal features. However, the two problems are quite different, i.e., the objective is not signal reconstruction but rather minimizing bit error rate. This generally results in different design rules for optimizing performance. We show that wavelet de-noising can be effectively used for data demodulation and we propose simple design rules for its implementation.</abstract><pub>IEEE</pub><doi>10.1109/ACSSC.1995.540878</doi></addata></record> |
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| identifier | ISSN: 1058-6393 |
| ispartof | Conference Record of The Twenty-Ninth Asilomar Conference on Signals, Systems and Computers, 1995, Vol.2, p.1142-1146 vol.2 |
| issn | 1058-6393 2576-2303 |
| language | eng |
| recordid | cdi_ieee_primary_540878 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | AWGN Bit error rate Demodulation Noise reduction Sampling methods Signal reconstruction Timing Wavelet coefficients Wavelet domain Wavelet transforms |
| title | Application of wavelet de-noising to signal demodulation |
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