High Performance Significance Approximation Error Tolerance Adder for Image Processing Applications
Addition is one of the fundamental arithmetic operations which are used extensively in many VLSI systems such as microprocessors and application specific DSP architectures. In this paper, the Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) is constructed, which is efficient...
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Veröffentlicht in: | Journal of electronic testing 2016-06, Vol.32 (3), p.377-383 |
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description | Addition is one of the fundamental arithmetic operations which are used extensively in many VLSI systems such as microprocessors and application specific DSP architectures. In this paper, the Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) is constructed, which is efficient in terms of accuracy, power and area. While considering the elementary structure of an image processing applications, it is a combination of the multipliers and delays, which in turn are the combination of the adders. This research paper describes the Algorithmic strength reduction technique which leads to a reduction in hardware complexity by exploiting the significances. This transformation is basically implemented for the reduction in the power consumption and area efficient of Very Large Scale Integration (VLSI) design or iteration period in a programmable Digital Signal Processing (DSP) implementation. The significance approximation error tolerant adder is designed using full adder and approximate full adder cells with reduced complexity at the gate level. The performance of 16 bit conventional Carry Select Adder (CSLA), 16 bit Error Tolerant carry select Adder (ET-CSLA) and proposed Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) are compared. For all the 2
16
input combinations, comparison is made between existing and proposed CSLA adders and the error tolerance analysis is carried out for accuracy improvement. Application of image processing is carried out using proposed SAET-CSLA. |
doi_str_mv | 10.1007/s10836-016-5587-z |
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16
input combinations, comparison is made between existing and proposed CSLA adders and the error tolerance analysis is carried out for accuracy improvement. Application of image processing is carried out using proposed SAET-CSLA.</description><identifier>ISSN: 0923-8174</identifier><identifier>EISSN: 1573-0727</identifier><identifier>DOI: 10.1007/s10836-016-5587-z</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Approximation ; CAE) and Design ; Circuits and Systems ; Computer-Aided Engineering (CAD ; Digital signal processing ; Digital signal processors ; Electrical Engineering ; Electronics ; Engineering ; Errors ; Image processing ; Mathematical analysis ; Reduction ; Tolerances ; Very large scale integration</subject><ispartof>Journal of electronic testing, 2016-06, Vol.32 (3), p.377-383</ispartof><rights>Springer Science+Business Media New York 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c349t-ed64d012f75a473e3aea1d4b89409e7bc7e1fd7df8c2749cc0874214da69d5f3</citedby><cites>FETCH-LOGICAL-c349t-ed64d012f75a473e3aea1d4b89409e7bc7e1fd7df8c2749cc0874214da69d5f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10836-016-5587-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10836-016-5587-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Jothin, R.</creatorcontrib><creatorcontrib>Vasanthanayaki, C.</creatorcontrib><title>High Performance Significance Approximation Error Tolerance Adder for Image Processing Applications</title><title>Journal of electronic testing</title><addtitle>J Electron Test</addtitle><description>Addition is one of the fundamental arithmetic operations which are used extensively in many VLSI systems such as microprocessors and application specific DSP architectures. In this paper, the Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) is constructed, which is efficient in terms of accuracy, power and area. While considering the elementary structure of an image processing applications, it is a combination of the multipliers and delays, which in turn are the combination of the adders. This research paper describes the Algorithmic strength reduction technique which leads to a reduction in hardware complexity by exploiting the significances. This transformation is basically implemented for the reduction in the power consumption and area efficient of Very Large Scale Integration (VLSI) design or iteration period in a programmable Digital Signal Processing (DSP) implementation. The significance approximation error tolerant adder is designed using full adder and approximate full adder cells with reduced complexity at the gate level. The performance of 16 bit conventional Carry Select Adder (CSLA), 16 bit Error Tolerant carry select Adder (ET-CSLA) and proposed Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) are compared. For all the 2
16
input combinations, comparison is made between existing and proposed CSLA adders and the error tolerance analysis is carried out for accuracy improvement. Application of image processing is carried out using proposed SAET-CSLA.</description><subject>Approximation</subject><subject>CAE) and Design</subject><subject>Circuits and Systems</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Digital signal processing</subject><subject>Digital signal processors</subject><subject>Electrical Engineering</subject><subject>Electronics</subject><subject>Engineering</subject><subject>Errors</subject><subject>Image processing</subject><subject>Mathematical analysis</subject><subject>Reduction</subject><subject>Tolerances</subject><subject>Very large scale integration</subject><issn>0923-8174</issn><issn>1573-0727</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kE1LAzEQhoMoWKs_wNuCFy-r-dpNciyl2kLBgr2HNJldt2w3NWlB--vNuh5E8DQM8zwvw4vQLcEPBGPxGAmWrMwxKfOikCI_naERKQTLsaDiHI2woiyXRPBLdBXjFieHFuUI2XlTv2UrCJUPO9NZyF6bumuqxn4vk_0--I9mZw6N77JZCD5ka99CGK7OQciSmS12poZsFbyFGJuu7sU2ZfRavEYXlWkj3PzMMVo_zdbTeb58eV5MJ8vcMq4OObiSO0xoJQrDBQNmwBDHN1JxrEBsrABSOeEqaangylosBaeEO1MqV1RsjO6H2PTy-xHiQe-aaKFtTQf-GDWRtOBKMkISevcH3fpj6NJzmgjFhJKyoIkiA2WDjzFApfchVRE-NcG6b10PrevUuu5b16fk0MGJie1qCL-S_5W-AJdrhn8</recordid><startdate>20160601</startdate><enddate>20160601</enddate><creator>Jothin, R.</creator><creator>Vasanthanayaki, C.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>7XB</scope><scope>88I</scope><scope>88K</scope><scope>8AO</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F28</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>H8G</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M2P</scope><scope>M2T</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>S0W</scope></search><sort><creationdate>20160601</creationdate><title>High Performance Significance Approximation Error Tolerance Adder for Image Processing Applications</title><author>Jothin, R. ; 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In this paper, the Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) is constructed, which is efficient in terms of accuracy, power and area. While considering the elementary structure of an image processing applications, it is a combination of the multipliers and delays, which in turn are the combination of the adders. This research paper describes the Algorithmic strength reduction technique which leads to a reduction in hardware complexity by exploiting the significances. This transformation is basically implemented for the reduction in the power consumption and area efficient of Very Large Scale Integration (VLSI) design or iteration period in a programmable Digital Signal Processing (DSP) implementation. The significance approximation error tolerant adder is designed using full adder and approximate full adder cells with reduced complexity at the gate level. The performance of 16 bit conventional Carry Select Adder (CSLA), 16 bit Error Tolerant carry select Adder (ET-CSLA) and proposed Significance Approximation Error Tolerant Carry Select Adder (SAET-CSLA) are compared. For all the 2
16
input combinations, comparison is made between existing and proposed CSLA adders and the error tolerance analysis is carried out for accuracy improvement. Application of image processing is carried out using proposed SAET-CSLA.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10836-016-5587-z</doi><tpages>7</tpages></addata></record> |
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subjects | Approximation CAE) and Design Circuits and Systems Computer-Aided Engineering (CAD Digital signal processing Digital signal processors Electrical Engineering Electronics Engineering Errors Image processing Mathematical analysis Reduction Tolerances Very large scale integration |
title | High Performance Significance Approximation Error Tolerance Adder for Image Processing Applications |
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