A Weighted Least-Square-Based Approach to FIR Filter Design Using the Frequency-Response Masking Technique

Lee, W.R.; Rehbock, Volker; Teo, K.L.; Caccetta, Louis

doi:10.1109/lsp.2004.830109

Cited by 21 publications

(31 citation statements)

References 6 publications

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“…The same is true for the design techniques in [4,7,12,19]. This filter is a Case A design with l 1 = 4, θ 1 = 0.4π , and φ 1 = 0.442π .…”

Section: One-stage Designmentioning

confidence: 90%

“…Because there are only few candidates of the L r 's left, and the estimated subfilter orders are very close to the actual orders that minimize the arithmetic complexity, the proposed overall optimization algorithm has to be run very few times. This fact makes the proposed algorithm drastically quicker compared with other existing ones [3,4,7,12,16,19,20], which do not exploit the above-mentioned observations at all.…”

Section: Estimation Of the Design Parameters For The Proposed Synthesmentioning

confidence: 97%

“…4 It should be pointed out that the estimated orders of the subfilters are very seldom the ones, by which the overall design, after the further optimization of following subsection, both meets the given overall criteria and minimizes the arithmetic complexity. Hence, these orders should be varied in the vicinity of the initial selections in the manner to be described in Sect.…”

Section: Algorithm For Finding An Initial Filtermentioning

confidence: 99%

“…Consider the following specifications [4,7,11,13,15,17,19]: ω p = 0.4π , ω s = 0.402π , δ p = 0.01, and δ s = 0.001. For the conventional direct-form FIR filter, the minimum order to meet the given criteria is 7 2558, requiring 1290 multipliers and 2558 adders when the coefficient symmetry is exploited.…”

Section: Filter Specificationsmentioning

confidence: 99%

“…This filter is a Case A design with l 1 = 4, θ 1 = 0.4π , and φ 1 = 0.442π . In [4,7,15,19], the minimum orders for G 6 |Ω| denotes the size of the set Ω. 7 Using the formula given in [2], the estimated order for the conventional direct-form FIR filter is 2542.…”

Section: One-stage Designmentioning

confidence: 99%

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An Efficient Algorithm for the Optimization of FIR Filters Synthesized Using the Multistage Frequency-Response Masking Approach

Yli‐Kaakinen

Saramäki

2010

Circuits Syst Signal Process

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A very efficient technique to drastically reduce the number of multipliers and adders in narrow transition-band linear-phase finite-impulse response digital filters is to use the one-stage or multistage frequency-response masking (FRM) approach, which has been originally introduced by Lim and further improved by Lim and Lian. In these original synthesis techniques, the subfilters in the overall implementation are separately designed. As shown earlier by the authors of this contribution together with Johansson, the arithmetic complexity in one-stage FRM filter designs can be considerably reduced by using the following two-step technique for simultaneously optimizing all the subfilters. First, a suboptimal solution is found by using a simple design scheme. Second, this solution is used as a start-up solution for further optimization, which is carried out with the aid of an efficient nonlinear optimization algorithm. This paper exploits this approach to synthesizing multistage FRM filters. An example taken from the literature illustrates that both the number of multipliers and the number of adders for the resulting optimized multistage FRM filters are approximately 70 percent compared with those of the filters synthesized using the original multistage FRM filter design schemes. Additional examples are included in order to show the benefits provided by the proposed synthesis scheme over other recently published design techniques, in terms of an improved performance of Some parts of this paper were presented at 158 Circuits Syst Signal Process (2011) 30: 157-183 the resulting solution, a higher accuracy of the solution, and a faster speed required to arrive at the best solution.

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“…The same is true for the design techniques in [4,7,12,19]. This filter is a Case A design with l 1 = 4, θ 1 = 0.4π , and φ 1 = 0.442π .…”

Section: One-stage Designmentioning

confidence: 90%

Section: Estimation Of the Design Parameters For The Proposed Synthesmentioning

confidence: 97%

Section: Algorithm For Finding An Initial Filtermentioning

confidence: 99%

Section: Filter Specificationsmentioning

confidence: 99%

Section: One-stage Designmentioning

confidence: 99%

See 3 more Smart Citations

An Efficient Algorithm for the Optimization of FIR Filters Synthesized Using the Multistage Frequency-Response Masking Approach

Yli‐Kaakinen

Saramäki

2010

Circuits Syst Signal Process

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Neural Network Approach for Designing One- and Two-Dimensional Quasi-Equiripple FIR Digital Filters

Wang

Yu-lou

Advances in Neural Networks – ISNN 2007

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Design Equations for Jointly Optimized Frequency-Response Masking Filters

Lian

2007

Circuits Syst Signal Process

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The introduction of nonlinear optimization techniques to the design of a frequency-response masking (FRM) filter has changed the way in which an FRM filter is synthesized. It allows all subfilters in an FRM structure to be optimized jointly, resulting in further savings in the number of arithmetic operations. Under the joint optimization, a new set of design equations is necessary, not only for a more computationally efficient filter, but also for the simplification of the design process and the reduction of the design time. In this paper, we present a set of design equations that estimates the filter lengths and optimum interpolation factor in an FRM filter under joint optimization. It is shown, by means of examples, that the proposed design equations lead to a better estimation of the optimum interpolation factor compared with existing design equations.

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A Weighted Least-Square-Based Approach to FIR Filter Design Using the Frequency-Response Masking Technique

Cited by 21 publications

References 6 publications

An Efficient Algorithm for the Optimization of FIR Filters Synthesized Using the Multistage Frequency-Response Masking Approach

An Efficient Algorithm for the Optimization of FIR Filters Synthesized Using the Multistage Frequency-Response Masking Approach

Neural Network Approach for Designing One- and Two-Dimensional Quasi-Equiripple FIR Digital Filters

Design Equations for Jointly Optimized Frequency-Response Masking Filters

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