Low-power CSD linear phase FIR filter structure using vertical common sub-expression

Jang, Young-Beom; Yang, Sejung

doi:10.1049/el:20020529

Cited by 54 publications

(57 citation statements)

References 2 publications

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“…In Fig. 4, for Q(1, 2)= [10,8], we get R=2 and J=6. Hence, bit i=1 can make a subexpression with bit J=6.…”

Section: R Findindex Min K J Rmentioning

confidence: 87%

“…Hence, additional LOs are required to implement the second half of the coefficients as symmetry cannot be exploited fully if VCSs are used for CSE. Hence, the hardware requirement and logical depth shown in [3], [8], and [10] are not sufficiently accurate [1]. The constraints discussed in this paper are not applicable to antisymmetric filters.…”

Section: Existing Methodsmentioning

confidence: 92%

“…The LD is reduced to 17.6% and 3.2%, respectively, compared to the results in [3] and [10]. By considering the implementation of the first half of the coefficients only, and assuming that the remaining half of the coefficients are symmetric to the first half so that their output can be shared, the authors in [3], [8], and [10], ignored the fact that VCSs put constraints on this sharing of output [1].…”

Section: Existing Methodsmentioning

confidence: 99%

“…By considering the implementation of the first half of the coefficients only, and assuming that the remaining half of the coefficients are symmetric to the first half so that their output can be shared, the authors in [3], [8], and [10], ignored the fact that VCSs put constraints on this sharing of output [1]. Hence, additional LOs are required to implement the second half of the coefficients as symmetry cannot be exploited fully if VCSs are used for CSE.…”

Section: Existing Methodsmentioning

confidence: 99%

“…We also use common subexpression elimination (CSE) to eliminate the redundant computations that exist in an MB by locating the most common bit patterns, called common subexpression (CS), existing in the binary representation of coefficients. Most authors have used canonical sign digit (CSD) representation to represent the coefficients [1]- [10]. In the CSD code of a number, each bit is set to 0, 1, or -1 so as to minimize the total number of nonzero An Improved Non-CSD 2-Bit Recursive Common Subexpression Elimination Method to Implement FIR Filter…”

Section: Introductionmentioning

confidence: 99%

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An Improved Non-CSD 2-Bit Recursive Common Subexpression Elimination Method to Implement FIR Filter

Hassan¹

2011

ETRI J

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The number of adders and critical paths in a multiplier block of a multiple constant multiplication based implementation of a finite impulse response (FIR) filter can be minimized through common subexpression elimination (CSE) techniques. A two-bit common subexpression (CS) can be located recursively in a noncanonic sign digit (CSD) representation of the filter coefficients. An efficient algorithm is presented in this paper to improve the elimination of a CS from the multiplier block of an FIR filter so that it can be realized with fewer adders and low logical depth as compared to the existing CSE methods in the literature. Vinod and others claimed the highest reduction in the number of logical operators (LOs) without increasing the logic depth (LD) requirement. Using the design examples given by Vinod and others, we compare the average reduction in LOs and LDs achieved by our algorithm. Our algorithm shows average LO improvements of 30.8%, 5.5%, and 22.5% with a comparative LD requirement over that of Vinod and others for three design examples. Improvement increases as the filter order increases, and for the highest filter order and lowest coefficient width, the LO improvements are 70.3%, 75.3%, and 72.2% for the three design examples.

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“…In Fig. 4, for Q(1, 2)= [10,8], we get R=2 and J=6. Hence, bit i=1 can make a subexpression with bit J=6.…”

Section: R Findindex Min K J Rmentioning

confidence: 87%