Internal quantization in FIR filters implemented using Multiple Constant Multiplications
This paper introduces an approach for quantizing intermediate values within an Multiple Constant Multiplication (MCM) implementation of a finite impulse response (FIR) filter. For a fixed-point Digital Signal Processing implementation, finite wordlength behavior in digital filter is very important....
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| creator | Guifeng Liu DeBrunner, L S DeBrunner, V Johansson, K |
| description | This paper introduces an approach for quantizing intermediate values within an Multiple Constant Multiplication (MCM) implementation of a finite impulse response (FIR) filter. For a fixed-point Digital Signal Processing implementation, finite wordlength behavior in digital filter is very important. We proposed an approach to reduce the quantization noise at the filter output while maintaining performance and keeping space requirements low. This approach is based on calculating the sensitivity of each node. By selectively adding 2 more bits to the high sensitivity nodes to store intermediate information for a 22 nd order half-band filter, the final output noise of FIR filter is reduced up to 40%. Considering the error distribution after each operation provides insight into the effects of quantization. |
| doi_str_mv | 10.1109/ACSSC.2010.5757738 |
| format | Conference Proceeding |
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For a fixed-point Digital Signal Processing implementation, finite wordlength behavior in digital filter is very important. We proposed an approach to reduce the quantization noise at the filter output while maintaining performance and keeping space requirements low. This approach is based on calculating the sensitivity of each node. By selectively adding 2 more bits to the high sensitivity nodes to store intermediate information for a 22 nd order half-band filter, the final output noise of FIR filter is reduced up to 40%. 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For a fixed-point Digital Signal Processing implementation, finite wordlength behavior in digital filter is very important. We proposed an approach to reduce the quantization noise at the filter output while maintaining performance and keeping space requirements low. This approach is based on calculating the sensitivity of each node. By selectively adding 2 more bits to the high sensitivity nodes to store intermediate information for a 22 nd order half-band filter, the final output noise of FIR filter is reduced up to 40%. Considering the error distribution after each operation provides insight into the effects of quantization.</description><subject>Adders</subject><subject>Digital signal processing</subject><subject>Finite impulse response filter</subject><subject>FIR filter</subject><subject>multiple constant multiplication</subject><subject>Noise</subject><subject>noise energy</subject><subject>Quantization</subject><subject>Sensitivity</subject><subject>Signal processing algorithms</subject><issn>1058-6393</issn><issn>2576-2303</issn><isbn>1424497221</isbn><isbn>9781424497225</isbn><isbn>9781424497201</isbn><isbn>1424497213</isbn><isbn>9781424497218</isbn><isbn>1424497205</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kM1OwzAQhM2fRCh5Abj4BVJsr3-PVUShUhES7YFbFScOMkrcEicHeHosaPey2vlm5rAI3VEyp5SYh0W52ZRzRtItlFAK9BnKjdKUM86NSuAcZUwoWTAgcIFuToDRS5RRInQhwcA1ymP8JGmkNJqzDL2vwuiGUHX4a6rC6H-q0e8D9gEvV2-49V2iEfv-0LneJWuDp-jDB36ZutEnEZf7EMeUPCm-_muIt-iqrbro8uOeoe3ycVs-F-vXp1W5WBeeKjEWzlrjOLWga6GdJbaF2lRN67hUUjdE2JpRAqwGoQGEtZw7aYk21NRSMZih-_9a75zbHQbfV8P37vgj-AW1R1f4</recordid><startdate>201011</startdate><enddate>201011</enddate><creator>Guifeng Liu</creator><creator>DeBrunner, L S</creator><creator>DeBrunner, V</creator><creator>Johansson, K</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201011</creationdate><title>Internal quantization in FIR filters implemented using Multiple Constant Multiplications</title><author>Guifeng Liu ; DeBrunner, L S ; DeBrunner, V ; Johansson, K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-ebb9e41b38c58eb0bf3c9adfe46768d05bc21032c358335bb44e6b08919c6723</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adders</topic><topic>Digital signal processing</topic><topic>Finite impulse response filter</topic><topic>FIR filter</topic><topic>multiple constant multiplication</topic><topic>Noise</topic><topic>noise energy</topic><topic>Quantization</topic><topic>Sensitivity</topic><topic>Signal processing algorithms</topic><toplevel>online_resources</toplevel><creatorcontrib>Guifeng Liu</creatorcontrib><creatorcontrib>DeBrunner, L S</creatorcontrib><creatorcontrib>DeBrunner, V</creatorcontrib><creatorcontrib>Johansson, K</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Guifeng Liu</au><au>DeBrunner, L S</au><au>DeBrunner, V</au><au>Johansson, K</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Internal quantization in FIR filters implemented using Multiple Constant Multiplications</atitle><btitle>2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers</btitle><stitle>ACSSC</stitle><date>2010-11</date><risdate>2010</risdate><spage>1284</spage><epage>1287</epage><pages>1284-1287</pages><issn>1058-6393</issn><eissn>2576-2303</eissn><isbn>1424497221</isbn><isbn>9781424497225</isbn><eisbn>9781424497201</eisbn><eisbn>1424497213</eisbn><eisbn>9781424497218</eisbn><eisbn>1424497205</eisbn><abstract>This paper introduces an approach for quantizing intermediate values within an Multiple Constant Multiplication (MCM) implementation of a finite impulse response (FIR) filter. For a fixed-point Digital Signal Processing implementation, finite wordlength behavior in digital filter is very important. We proposed an approach to reduce the quantization noise at the filter output while maintaining performance and keeping space requirements low. This approach is based on calculating the sensitivity of each node. By selectively adding 2 more bits to the high sensitivity nodes to store intermediate information for a 22 nd order half-band filter, the final output noise of FIR filter is reduced up to 40%. Considering the error distribution after each operation provides insight into the effects of quantization.</abstract><pub>IEEE</pub><doi>10.1109/ACSSC.2010.5757738</doi><tpages>4</tpages></addata></record> |
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| identifier | ISSN: 1058-6393 |
| ispartof | 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers, 2010, p.1284-1287 |
| issn | 1058-6393 2576-2303 |
| language | eng |
| recordid | cdi_ieee_primary_5757738 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Adders Digital signal processing Finite impulse response filter FIR filter multiple constant multiplication Noise noise energy Quantization Sensitivity Signal processing algorithms |
| title | Internal quantization in FIR filters implemented using Multiple Constant Multiplications |
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