Bit-level multiplierless FIR filter optimization incorporating sparse filter technique

Multiplierless FIR filter optimization has been extensively studied in the past decades to minimize the number of adders. A more accurate measurement of the implementation complexity is the number of full adders counted at bit-level. However, the high computational complexity of the optimization at...

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Main Authors: Ye, Wen Bin, Yu, Ya Jun
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2014
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Online Access:https://hdl.handle.net/10356/103630
http://hdl.handle.net/10220/24502
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1036302020-03-07T14:00:37Z Bit-level multiplierless FIR filter optimization incorporating sparse filter technique Ye, Wen Bin Yu, Ya Jun School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits Multiplierless FIR filter optimization has been extensively studied in the past decades to minimize the number of adders. A more accurate measurement of the implementation complexity is the number of full adders counted at bit-level. However, the high computational complexity of the optimization at bit-level hinders the technique from practical applications. In this paper, the sparse filter technique is exploited and makes the search space at bit-level significantly reduced. Thus, the bit-level optimization of multiplierless FIR filters for the first time becomes possible. When the sparse filter technique is employed for the multiplierless filter design, the sparsity of the filter is properly controlled so that the feasibility of the bit-level optimization in discrete space is maintained. Thereafter, in the reduced search space, a tree search algorithm is formulated at bit-level, and techniques to estimate the bit level hardware cost and to accelerate the search are presented. Design examples show that the proposed bit-level optimization method generates designs with lower hardware cost and power consumption than that of the best word-level optimization methods, while the design time is still at an acceptable level. The average power savings to 3 recent published techniques are 13.6%, 8.0% and 26.1%, respectively. Accepted version 2014-12-22T02:14:54Z 2019-12-06T21:16:41Z 2014-12-22T02:14:54Z 2019-12-06T21:16:41Z 2014 2014 Journal Article Ye, W. B. & Yu, Y. J. (2014). Bit-level multiplierless FIR filter optimization incorporating sparse filter technique. IEEE transactions on circuits and systems I : regular papers, 61(11), 3206 - 3215. 1549-8328 https://hdl.handle.net/10356/103630 http://hdl.handle.net/10220/24502 10.1109/TCSI.2014.2327287 en IEEE transactions on circuits and systems I : regular papers © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TCSI.2014.2327287]. 11 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Electronic circuits
Ye, Wen Bin
Yu, Ya Jun
Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
description Multiplierless FIR filter optimization has been extensively studied in the past decades to minimize the number of adders. A more accurate measurement of the implementation complexity is the number of full adders counted at bit-level. However, the high computational complexity of the optimization at bit-level hinders the technique from practical applications. In this paper, the sparse filter technique is exploited and makes the search space at bit-level significantly reduced. Thus, the bit-level optimization of multiplierless FIR filters for the first time becomes possible. When the sparse filter technique is employed for the multiplierless filter design, the sparsity of the filter is properly controlled so that the feasibility of the bit-level optimization in discrete space is maintained. Thereafter, in the reduced search space, a tree search algorithm is formulated at bit-level, and techniques to estimate the bit level hardware cost and to accelerate the search are presented. Design examples show that the proposed bit-level optimization method generates designs with lower hardware cost and power consumption than that of the best word-level optimization methods, while the design time is still at an acceptable level. The average power savings to 3 recent published techniques are 13.6%, 8.0% and 26.1%, respectively.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Ye, Wen Bin
Yu, Ya Jun
format Article
author Ye, Wen Bin
Yu, Ya Jun
author_sort Ye, Wen Bin
title Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
title_short Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
title_full Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
title_fullStr Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
title_full_unstemmed Bit-level multiplierless FIR filter optimization incorporating sparse filter technique
title_sort bit-level multiplierless fir filter optimization incorporating sparse filter technique
publishDate 2014
url https://hdl.handle.net/10356/103630
http://hdl.handle.net/10220/24502
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