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Journal ArticleDOI

Frequency-response masking approach for the synthesis of sharp linear phase digital filters

TLDR
If the frequency responses of the original ( M + 1) -band filter and its complementary filter are properly masked and recombined, narrow transition-band filter can be obtained and this technique can be used to design sharp low-pass, high- pass, bandpass, and bandstop filters with arbitrary passband bandwidth.
Abstract
If each delay element of a linear phase low-pass digital filter is replaced by M delay elements, an (M + 1) -band filter is produced. The transition-width of this (M + 1) -band filter is 1/M that of the prototype low-pass filter. A complementary filter can be obtained by subtracting the output of the (M + 1) -band filter from a suitably delayed version of the input. The complementary filter is an (M + 1) -band filter whose passbands and stopbands are the stopbands and passbands, respectively, of the original (M + 1) -band filter. If the frequency responses of the original ( M + 1) -band filter and its complementary filter are properly masked and recombined, narrow transition-band filter can be obtained. This technique can be used to design sharp low-pass, high-pass, bandpass, and bandstop filters with arbitrary passband bandwidth.

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Citations
More filters
Journal ArticleDOI

Design of computationally efficient interpolated FIR filters

TL;DR: In this article, the number of multipliers required in the implementation of interpolated FIR (Finite-impulse response) filters in the form H(Z)=F(z/sup L/)G(z) is studied.
Journal ArticleDOI

The optimum design of one- and two-dimensional FIR filters using the frequency response masking technique

TL;DR: In this paper, an expression for the impulse response up-sampling ratio M, which will produce a minimum complexity design, is derived, and an optimum design relationship for the interpolated impulse response technique is also derived.
Journal ArticleDOI

Linear Programming Algorithms for Sparse Filter Design

TL;DR: This paper describes several approximate polynomial-time algorithms that use linear programming to design filters having a small number of nonzero coefficients, i.e., filters that are sparse.
Journal ArticleDOI

Frequency-response masking approach for digital filter design: complexity reduction via masking filter factorization

TL;DR: In this paper, the authors presented three methods for reducing the complexity of the masking filters, which can be realized as a cascade of a common subfilter and a pair of equalizers.
Proceedings ArticleDOI

Coefficient decimation approach for realizing reconfigurable finite impulse response filters

TL;DR: A new approach to implement computationally efficient reconfigurable finite impulse response (FIR) filter is presented in this paper and the design of a reconfigured filter bank using the above approach is shown.
References
More filters
Journal ArticleDOI

FIR filter design over a discrete powers-of-two coefficient space

TL;DR: In this article, a digital filter with discrete coefficient values selected from the powers-of-two coefficient space is designed using the methods of integer programming, and the frequency responses obtained are shown to be superior to those obtained by simply rounding the coefficients.
Journal ArticleDOI

Interpolated finite impulse response filters

TL;DR: In this article, a cascade of two sections is proposed for finite impulse response (FIR) digital filters, where the first section generates a sparse set of impulse response samples and the other section generates the remaining samples by using interpolation.
Journal ArticleDOI

FIR digital filter design techniques using weighted Chebyshev approximation

TL;DR: In this article, various approaches to designing FIR digital filters using the theory of weighted Chebyshev approximation are discussed and compared on the basis of their capabilities and limitations, and the relationships between filter parameters are briefly discussed for the case of low-pass filters.
Journal ArticleDOI

Discrete coefficient FIR digital filter design based upon an LMS criteria

TL;DR: In this article, the remaining unquantized coefficients of a FIR linear phase digital filter when one or more of the filter coefficients takes on discrete values are optimized using the least square response error.
Journal ArticleDOI

Optimum FIR digital filter implementations for decimation, interpolation, and narrow-band filtering

TL;DR: In this article, a general theory of multistage decimators and interpolators for sampling rate reduction and sampling rate increase is presented, and a set of curves and necessary relations for optimally designing multi-stage decimator is also given.
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