Adaptation of an all-pass equalizer for decision feedback equalization
Recording channels using decision feedback equalization require a minimum phase response and white noise at the detector to achieve maximum signal-to-noise ratio. A low order all-pass filter can equalize the feedforward path so that it approximately achieves a minimum phase response. In this paper,...
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| Veröffentlicht in: | IEEE transactions on magnetics 1999-03, Vol.35 (2), p.1083-1090 |
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| container_end_page | 1090 |
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| container_issue | 2 |
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| container_title | IEEE transactions on magnetics |
| container_volume | 35 |
| creator | Wiedmann, R. Kennei, J.G. Kolodziej, W.J. |
| description | Recording channels using decision feedback equalization require a minimum phase response and white noise at the detector to achieve maximum signal-to-noise ratio. A low order all-pass filter can equalize the feedforward path so that it approximately achieves a minimum phase response. In this paper, we describe an adaptive algorithm for iteratively determining the optimal transfer function of the all-pass filter. Adaptation is based on estimating the gradient of the mean-square error with respect to the poles of the filter. This estimate is then used to update the positions of the poles. One simplifying feature of this technique is that these gradients are determined by applying the output of the all-pass to low-order finite impulse response (FIR) filters. We do not require values from the internal states of the filter. The proposed adaptation algorithm is characterized for first- and second-order all-pass filters over a range of storage densities. The optimality of the resulting equalizer is evaluated as a function of the order of the FLR filters used in estimating the gradients. |
| doi_str_mv | 10.1109/20.748857 |
| format | Article |
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A low order all-pass filter can equalize the feedforward path so that it approximately achieves a minimum phase response. In this paper, we describe an adaptive algorithm for iteratively determining the optimal transfer function of the all-pass filter. Adaptation is based on estimating the gradient of the mean-square error with respect to the poles of the filter. This estimate is then used to update the positions of the poles. One simplifying feature of this technique is that these gradients are determined by applying the output of the all-pass to low-order finite impulse response (FIR) filters. We do not require values from the internal states of the filter. The proposed adaptation algorithm is characterized for first- and second-order all-pass filters over a range of storage densities. The optimality of the resulting equalizer is evaluated as a function of the order of the FLR filters used in estimating the gradients.</description><identifier>ISSN: 0018-9464</identifier><identifier>EISSN: 1941-0069</identifier><identifier>DOI: 10.1109/20.748857</identifier><identifier>CODEN: IEMGAQ</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Adaptation ; Applied sciences ; Decision feedback equalizers ; Density ; Detectors ; Electronics ; Equalization ; Equalizers ; Estimating ; Exact sciences and technology ; Feedback ; Finite impulse response filter ; IIR filters ; Impulse response ; Intersymbol interference ; Magnetic devices ; Magnetic recording ; Magnetic separation ; Maximum likelihood detection ; Other magnetic recording and storage devices (including tapes, disks, and drums) ; Phase detection ; Poles ; Semiconductor electronics. Microelectronics. Optoelectronics. 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A low order all-pass filter can equalize the feedforward path so that it approximately achieves a minimum phase response. In this paper, we describe an adaptive algorithm for iteratively determining the optimal transfer function of the all-pass filter. Adaptation is based on estimating the gradient of the mean-square error with respect to the poles of the filter. This estimate is then used to update the positions of the poles. One simplifying feature of this technique is that these gradients are determined by applying the output of the all-pass to low-order finite impulse response (FIR) filters. We do not require values from the internal states of the filter. The proposed adaptation algorithm is characterized for first- and second-order all-pass filters over a range of storage densities. The optimality of the resulting equalizer is evaluated as a function of the order of the FLR filters used in estimating the gradients.</description><subject>Adaptation</subject><subject>Applied sciences</subject><subject>Decision feedback equalizers</subject><subject>Density</subject><subject>Detectors</subject><subject>Electronics</subject><subject>Equalization</subject><subject>Equalizers</subject><subject>Estimating</subject><subject>Exact sciences and technology</subject><subject>Feedback</subject><subject>Finite impulse response filter</subject><subject>IIR filters</subject><subject>Impulse response</subject><subject>Intersymbol interference</subject><subject>Magnetic devices</subject><subject>Magnetic recording</subject><subject>Magnetic separation</subject><subject>Maximum likelihood detection</subject><subject>Other magnetic recording and storage devices (including tapes, disks, and drums)</subject><subject>Phase detection</subject><subject>Poles</subject><subject>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</subject><subject>Transfer functions</subject><issn>0018-9464</issn><issn>1941-0069</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNqN0D1PwzAQBmALgUQpDKxMGRCCIcVnO_4Yq4oCUiUWmKOLc5ECaZLG6QC_npQU2BDT6XTPvcPL2DnwGQB3t4LPjLI2MQdsAk5BzLl2h2zCOdjYKa2O2UkIr8OqEuATtpzn2PbYl00dNUWEdYRVFbcYQkSbLVblB3VR0XRRTr4MO1UQ5Rn6t-_71-8pOyqwCnS2n1P2srx7XjzEq6f7x8V8FXtpeB9r0C7hOVksBJrMCwsFoTaEMskEeek5zw1piaS1ssCzgQ9S5d7YXAk5ZVdjbts1my2FPl2XwVNVYU3NNqTCCiGl-wfUTnANMMDrPyFoA0K6BNxAb0bquyaEjoq07co1du8p8HTXfip4OrY_2Mt9LAaPVdFhPfT3-2DAGb2LvBhZSUQ_133GJ9Lvivk</recordid><startdate>19990301</startdate><enddate>19990301</enddate><creator>Wiedmann, R.</creator><creator>Kennei, J.G.</creator><creator>Kolodziej, W.J.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JG9</scope><scope>L7M</scope></search><sort><creationdate>19990301</creationdate><title>Adaptation of an all-pass equalizer for decision feedback equalization</title><author>Wiedmann, R. ; Kennei, J.G. ; Kolodziej, W.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c370t-616950de8af2a7bc281fea67ea35b2ec3c00d7e63ae664810b9502a74dc78d423</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Adaptation</topic><topic>Applied sciences</topic><topic>Decision feedback equalizers</topic><topic>Density</topic><topic>Detectors</topic><topic>Electronics</topic><topic>Equalization</topic><topic>Equalizers</topic><topic>Estimating</topic><topic>Exact sciences and technology</topic><topic>Feedback</topic><topic>Finite impulse response filter</topic><topic>IIR filters</topic><topic>Impulse response</topic><topic>Intersymbol interference</topic><topic>Magnetic devices</topic><topic>Magnetic recording</topic><topic>Magnetic separation</topic><topic>Maximum likelihood detection</topic><topic>Other magnetic recording and storage devices (including tapes, disks, and drums)</topic><topic>Phase detection</topic><topic>Poles</topic><topic>Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices</topic><topic>Transfer functions</topic><toplevel>online_resources</toplevel><creatorcontrib>Wiedmann, R.</creatorcontrib><creatorcontrib>Kennei, J.G.</creatorcontrib><creatorcontrib>Kolodziej, W.J.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Materials Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE transactions on magnetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wiedmann, R.</au><au>Kennei, J.G.</au><au>Kolodziej, W.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptation of an all-pass equalizer for decision feedback equalization</atitle><jtitle>IEEE transactions on magnetics</jtitle><stitle>TMAG</stitle><date>1999-03-01</date><risdate>1999</risdate><volume>35</volume><issue>2</issue><spage>1083</spage><epage>1090</epage><pages>1083-1090</pages><issn>0018-9464</issn><eissn>1941-0069</eissn><coden>IEMGAQ</coden><abstract>Recording channels using decision feedback equalization require a minimum phase response and white noise at the detector to achieve maximum signal-to-noise ratio. A low order all-pass filter can equalize the feedforward path so that it approximately achieves a minimum phase response. In this paper, we describe an adaptive algorithm for iteratively determining the optimal transfer function of the all-pass filter. Adaptation is based on estimating the gradient of the mean-square error with respect to the poles of the filter. This estimate is then used to update the positions of the poles. One simplifying feature of this technique is that these gradients are determined by applying the output of the all-pass to low-order finite impulse response (FIR) filters. We do not require values from the internal states of the filter. The proposed adaptation algorithm is characterized for first- and second-order all-pass filters over a range of storage densities. The optimality of the resulting equalizer is evaluated as a function of the order of the FLR filters used in estimating the gradients.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/20.748857</doi><tpages>8</tpages></addata></record> |
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| ispartof | IEEE transactions on magnetics, 1999-03, Vol.35 (2), p.1083-1090 |
| issn | 0018-9464 1941-0069 |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptation Applied sciences Decision feedback equalizers Density Detectors Electronics Equalization Equalizers Estimating Exact sciences and technology Feedback Finite impulse response filter IIR filters Impulse response Intersymbol interference Magnetic devices Magnetic recording Magnetic separation Maximum likelihood detection Other magnetic recording and storage devices (including tapes, disks, and drums) Phase detection Poles Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices Transfer functions |
| title | Adaptation of an all-pass equalizer for decision feedback equalization |
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