Two High-Performance Adaptive Filter Implementation Schemes Using Distributed Arithmetic
Distributed arithmetic (DA) is performed to design bit-level architectures for vector-vector multiplication with a direct application for the implementation of convolution, which is necessary for digital filters. In this brief, two novel DA-based implementation schemes are proposed for adaptive fini...
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| Vydáno v: | IEEE transactions on circuits and systems. II, Express briefs Ročník 58; číslo 9; s. 600 - 604 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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New York
IEEE
01.09.2011
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1549-7747, 1558-3791 |
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| Abstract | Distributed arithmetic (DA) is performed to design bit-level architectures for vector-vector multiplication with a direct application for the implementation of convolution, which is necessary for digital filters. In this brief, two novel DA-based implementation schemes are proposed for adaptive finite-impulse response filters. Different from conventional DA techniques, our proposed schemes use coefficients as addresses to access a series of lookup tables (LUTs) storing sums of delayed and scaled input samples. Two smart LUT updating methods are developed, and least-mean-square adaptation is performed to update the weights and minimize the mean square error between the estimated and desired output. Results show that our two high-performance designs achieve high speed, low computation complexities, and low area cost. |
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| AbstractList | Distributed arithmetic (DA) is performed to design bit-level architectures for vector-vector multiplication with a direct application for the implementation of convolution, which is necessary for digital filters. In this brief, two novel DA-based implementation schemes are proposed for adaptive finite-impulse response filters. Different from conventional DA techniques, our proposed schemes use coefficients as addresses to access a series of lookup tables (LUTs) storing sums of delayed and scaled input samples. Two smart LUT updating methods are developed, and least-mean-square adaptation is performed to update the weights and minimize the mean square error between the estimated and desired output. Results show that our two high-performance designs achieve high speed, low computation complexities, and low area cost. |
| Author | DeBrunner, L. S. Rui Guo |
| Author_xml | – sequence: 1 surname: Rui Guo fullname: Rui Guo email: rg07g@fsu.edu organization: Dept. of Electr. & Comput. Eng., Florida State Univ., Tallahassee, FL, USA – sequence: 2 givenname: L. S. surname: DeBrunner fullname: DeBrunner, L. S. email: linda.debrunner@fsu.edu organization: Dept. of Electr. & Comput. Eng., Florida State Univ., Tallahassee, FL, USA |
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| Cites_doi | 10.1109/TASSP.1974.1162619 10.1109/TASSP.1983.1164113 10.1109/TCS.1977.1084294 10.1109/53.29648 10.1049/ip-g-1.1986.0003 10.1109/ICASSP.2004.1327072 10.1109/TCSI.2005.851731 10.1109/TASSP.1986.1164956 10.1007/s11265-010-0479-4 10.1049/ip-f-1.1981.0040 10.1109/FCCM.2004.15 |
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| SubjectTerms | Adaptive filter Adaptive filters Arithmetic Circuits Design engineering Digital filters Digital signal processing distributed arithmetic (DA) Encoding Finite impulse response filter finite-impluse response (FIR) High speed least mean square (LMS) Least squares approximation lookup table (LUT) Lookup tables Mean square values multiply accumulate (MAC) offset-binary coding (OBC) Read only memory Speech processing Table lookup |
| Title | Two High-Performance Adaptive Filter Implementation Schemes Using Distributed Arithmetic |
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