Signal processor implementation of variable digital filters

Jarske, P.; Mitra, S.K.; Neuvo, Y.

doi:10.1109/19.7456

Cited by 36 publications

(13 citation statements)

References 14 publications

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“…To approximate , the 1-D transfer function (2) is used, and the optimal coefficients are found by minimizing the squared magnitude response error (3) where represent discrete frequencies, are the sampled magnitude responses of at points . However, it should be pointed out that the resulting may be unstable because the necessary and sufficient stability conditions (4) are not imposed on the denominator coefficients and . To overcome this difficulty, we first perform the variable substitutions (5) on the denominator coefficients [6].…”

Section: Design Methods and Stabilitymentioning

confidence: 99%

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Design of recursive 1-D variable filters with guaranteed stability

Deng

1997

IEEE Trans. Circuits Syst. II

115

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The digital filters with adjustable frequency-domain characteristics are called variable filters. Variable filters are used in many signal processing fields, but the recursive variable filters are extremely difficult to design due to the stability problem. This paper proposes a new method for designing recursive onedimensional (1-D) variable filters whose stability is guaranteed. The method finds the coefficients of the transfer function of a variable digital filter as the multidimensional (M-D) polynomials of a few variables. The variables specify different frequencydomain characteristics, thus, we call the variables the spectral parameters. In applying the resulting variable filters, substituting different values of the spectral parameters into the M-D polynomials will obtain different filter coefficients and, thus, obtain different frequency-domain characteristics. To guarantee the stability, we first perform coefficient substitutions on the denominator coefficients such that they satisfy the stability conditions. Then both denominator and numerator coefficients are determined as M-D polynomials. In determining the M-D polynomials, we also propose an efficient least-squares approximation method that requires only solving simultaneous linear equations. Two examples are given to show the effectiveness of the proposed variable filter design technique.

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Section: Design Methods and Stabilitymentioning

confidence: 99%

“…Especially in the past two decades, the design and implementation of variable filters have received considerable attention. Among the developed methods, many of them are based on frequency transformations [1]- [4]. By such methods, low-pass, bandpass, and high-pass variable filters with variable cutoff frequencies can be designed.…”

Section: Introductionmentioning

confidence: 99%

Design of recursive 1-D variable filters with guaranteed stability

Deng

1997

IEEE Trans. Circuits Syst. II

115

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“…Moreover, the stopband range to need a large attenuation characteristic is different according to the environments. However, previous method, [2]∼ [5], cannot design a VDF with changing a large attenuations in the stopband by using some spectral parameter. Then, we proposed a VDF with changing a piecewise large attenuation characteristic in the stopband [6].…”

Section: Introductionmentioning

confidence: 98%

Designing FIR filter with variable stopbands

Aikawa

Mori

2007

2007 14th IEEE International Conference on Electronics, Circuits and Systems

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In this paper, we define filters capable of changing frequency response as variable digital filters (VDFs). In the previous VDF having changed a piecewise large attenuation characteristic in the stopband, it is difficult to decrease the filter degree to two or more, changing noises. We propose a transfer function of FIR filters with changing some large attenuations in the stopband by using spectral parameters and its design method. The number of spectrum parameters used here uses the number of changing stopbands. In this method, the minimization problems are formulated as semidefinite programming (SDP) in the frequency domain. Moreover, we present that the proposed VDF can be implemented using Farrow structure. Finally, we confirm the effectiveness of this method through numerical examples.

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“…The methods for designing variable digital filters can be broadly classified into two categories, namely, frequency transformation methods [12][13][14][15] and spectral parameter approximation methods [3,[5][6][7][8][9][10][11]16]. The disadvantage of the methods, belonging into the former class, is that the edge frequencies and the ripples of the various bands cannot be independently controlled.…”

Section: Introductionmentioning

confidence: 99%

Efficient Recursive Digital Filters with Variable Magnitude Characteristics

Yli‐Kaakinen

Saramäki

2006

Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006

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This paper considers designing in the minimax sense complementary low-pass/high-pass recursive digitalfilters with variable magnitude characteristics. A filter structure based on the parallel connection of two variable fractional delay all-pass filters is proposed for implementing these filters. The filter optimization is performed in two basic steps. First, an initial filter is generated using a simple design scheme. Second, this filter is used as a start-up solution for further optimization being carried out by an efficient constrained nonlinear optimization algorithm. Examples are included for illustrating the efficiency of the proposed design scheme. In addition, the performance and the complexity of the proposed variable recursive digitalfilters are compared with those of the other variable recursive digital filters proposed in the literature. This comparison shows that the number of multipliers for the proposed filters is less than 15 percent compared with other existing structures.

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Signal processor implementation of variable digital filters

Cited by 36 publications

References 14 publications

Design of recursive 1-D variable filters with guaranteed stability

Design of recursive 1-D variable filters with guaranteed stability

Designing FIR filter with variable stopbands

Efficient Recursive Digital Filters with Variable Magnitude Characteristics

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