A simple design of FIR filters with powers-of-two coefficients

Zhao, Qingwei; Tadokoro, Yoshiaki

doi:10.1109/31.1785

Cited by 139 publications

(37 citation statements)

References 5 publications

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“…The difference is that now the filter coefficient values are very coarse and, as a consequence, the filter gain G assumes a particular relevance. Indeed, perfonnance may deteriorate up to 6 dB if the choice of G is not accurate [6]. The filter design then becomes a mixed optimization problem, namely, continuous in the filter gain, and discrete in the coefficient values.…”

Section: A Variable Spacementioning

confidence: 99%

“…As mentioned in the introduction, when filter coefficient space is very coarse, determination of the optimum value of the filter gain G is very important [6]. If…”

Section: A Design Of Fir Digital Filtersmentioning

confidence: 99%

“…To appreciate the similarities and differences with respect to our design strategy, Zhao and Tadokoro's method [6] is briefly reported. First, they determine the value of gain G by minimization of…”

Section: A Design Of Fir Digital Filtersmentioning

confidence: 99%

“…For higher order filters, we should mention the suboptimal design method of Zhao and Tadokoro [6] which first determines the filter gain, and then performs a local optimization of the filter coefficients in order to reduce the maximum weighted frequency error.…”

Section: Introductionmentioning

confidence: 99%

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Applications of simulated annealing for the design of special digital filters

Benvenuto

Marchesi

Uncini

1992

IEEE Trans. Signal Process.

133

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Abstract-This paper describes the salient features of using a simulated annealing (SA) algorithm in the context of designing digital filters with coefficient values expressed as the sum of power of two. A procedure for linear phase digital filter design, using this algorithm, is first presented and tested, yielding results as good as known optimal methods. The algorithm is then applied to the design of Nyquist filters, optimizing at the same time both frequency response and intersymbol interference, and to the design of cascade form FIR filters.Although SA is not a solution to all design problems, and is computationally very expensive, it may be an important method for designing special digital filters where numerous or conflicting constraints are present.

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Section: A Variable Spacementioning

confidence: 99%

“…As mentioned in the introduction, when filter coefficient space is very coarse, determination of the optimum value of the filter gain G is very important [6]. If…”

Section: A Design Of Fir Digital Filtersmentioning

confidence: 99%

Section: A Design Of Fir Digital Filtersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Applications of simulated annealing for the design of special digital filters

Benvenuto

Marchesi

Uncini

1992

IEEE Trans. Signal Process.

133

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“…A 28th order filter with an attenuation of -50.96 dB can be designed with 31 adders. To design a comparable (complexity) filter with 2 SPT terms per coefficient (as in [6]) we must consider a maximum of 20th order2, which gives an attenuation of about -36 dB (from [6]). Note that even an optimal floating point 20th order filter only achieves -39dB.…”

Section: V-430mentioning

confidence: 99%

Automated design of low complexity FIR filters

Redmill

Bull

ISCAS '98. Proceedings of the 1998 IEEE International Symposium on Circuits and Systems (Cat. No.98CH36187)

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This paper considers the design of low complexity FIR filters. Complexity is reduced by constraining the filters to have integer coefficients, which can be efficiently implemented using primitive operator directed graphs (PODG). Genetic Algorithms (GAS) are used in conjunction with a heuristic graph design algorithm, to provide a solution set which represents different compromises between performance, complexity and filter order.Example results are presented for both one and two dimensional filters, and are shown to provide both superior performance and complexity, compared to previous methods. The main benefits result from the use of a joint optimization, rather than a separable 2-stage approach. The use of a PODG representation is shown to provide significant improvements over a canonic signed digit (CSD) or signed power-of-two (SPT) representation.

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Optimal design of CSD coefficient FIR filters subject to number of nonzero digits

Ozaki

Suyama

2011

Elect Comm in Japan

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SUMMARYIn the hardware implementation of FIR (Finite Impulse Response) digital filters, it is desirable to reduce the total number of nonzero digits used for representation of the filter coefficients. In general, the design problem of FIR filters with CSD (Canonical Signed Digit) representation, which is efficient for reduction of the number of multiplier units, is often treated as a 0-1 combinational problem. In such problems, certain difficult constraints hinder linearization of the problem. Although many kinds of heuristic approaches have been used to solve the problem, the solutions obtained in such a manner cannot be guaranteed to be optimal. In this paper, we attempt to formulate the design problem as a 0-1 mixed integer linear programming problem and to solve it by using the branch and bound technique, which is a powerful method for solving integer programming problems. Several design examples are presented to illustrate the efficient performance of the proposed method.

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A simple design of FIR filters with powers-of-two coefficients

Cited by 139 publications

References 5 publications

Applications of simulated annealing for the design of special digital filters

Applications of simulated annealing for the design of special digital filters

Automated design of low complexity FIR filters

Optimal design of CSD coefficient FIR filters subject to number of nonzero digits

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