Peak-Error-Constrained Sparse FIR Filter Design Using Iterative SOCP

Jiang, Aimin; Kwan, Hon Keung; Zhu, Yanping

doi:10.1109/tsp.2012.2199316

Cited by 57 publications

(18 citation statements)

References 27 publications

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“…To tackle this problem, a great deal of effort has been made to develop efficient algorithms. In this paper, we can employ one of these sparse filter algorithms, for example, linear programming [15], iterative second-order cone programming (ISOCP) [16], iterative reweighted 1 (IRL1) [17], and iterative reweighted OMP (IROMP) schemes [9], to attain the desired sparse FIR single notch filter.…”

Section: ( )mentioning

confidence: 99%

A Novel Design of Sparse FIR Multiple Notch Filters with Tunable Notch Frequencies

Shi

et al. 2018

Mathematical Problems in Engineering

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We focus on the design of finite impulse response (FIR) multiple notch filters. To reduce the computational complexity and hardware implementation complexity, a novel algorithm is developed based on the mixture of the tuning of notch frequencies and the sparsity of filter coefficients. The proposed design procedure can be carried out as follow: first, since sparse FIR filters have lower implementation complexity than full filters, a sparse linear phase FIR single notch filter with the given rejection bandwidth and passband attenuation is designed. Second, a tuning procedure is applied to the computed sparse filter to produce the desired sparse linear phase FIR multiple notch filter. When the notch frequencies are varied, the same tuning procedure can be employed to render the new multiple notch filter instead of designing the filter from scratch. The effectiveness of the proposed algorithm is demonstrated through three design examples.

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Section: ( )mentioning

confidence: 99%

A Novel Design of Sparse FIR Multiple Notch Filters with Tunable Notch Frequencies

Shi

et al. 2018

Mathematical Problems in Engineering

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“…(A3) Design with the sparse filter schemes If one of the sparse filter design scheme [1] or [4] is employed to design F(e jω ) with its real-valued amplitude response defined in (2), the order N of F(e jω ) can also be estimated from (6).…”

Section: The Order Estimation Of Linear-phase Fir Narrow-band Low-pasmentioning

confidence: 99%

The Design of Linear-Phase FIR Multiple-Notch Filters with Variable Notch Frequencies

Zhao

Wang

2015

Circuits Syst Signal Process

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In this paper, a paradigm is developed to design the linear-phase FIR multiple-notch filters with variable notch frequencies. The design procedure can be proceeded through two steps: First, a linear-phase narrow-band low-pass filter met the given bandwidth and stopband ripple specifications is designed. Second, a tuning procedure is applied to the computed low-pass filter to yield the desired multiplenotch filter. When the notch frequencies are varied, the same tuning procedure can be employed to render the multiple-notch filter with the new set of the notch frequencies.The tuning procedure employed reduces the computational complexity of designing the multiple-notch filter with the new set of the notch frequencies. The simulation results demonstrate the effectiveness of our scheme.

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“…Based on the difference of impulse responses, digital filters can be categorized into two classes [1]: finite impulse response (FIR) filters [2]- [4] and infinite impulse response (IIR) filters [5]- [16]. Although the stability of FIR filters can be guaranteed, the order of FIR filters is generally higher than that of IIR filters.…”

Section: Introductionmentioning

confidence: 99%

A System Identification Based Approach for Design of IIR Digital Filters with Robust Stability

Nakamoto

Hirakawa

Yamamoto

2017

SICE Journal of Control, Measurement, and System Integration

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: Design problem of infinite impulse response (IIR) filters is generally a non-linear optimization problem due to the presence of denominator polynomial. Additionally, the stability condition (position of poles) must be considered when optimizing the filter coefficients. Hence, an iterative optimization is usually required to solve the design problem for stable IIR filter. In this paper, we present a new method for the design of IIR filters without iterative optimization. We employ a system identification method for time series signal where the input signal and its ideal output signal are generated by a Gaussian stochastic process with a prescribed frequency characteristic. Then, based on Parseval's theorem, we can obtain the IIR filter in the frequency domain. The advantage of the proposed method is to compute the IIR stable digital filters as a closed-form solution. That is, we can approximate the given frequency response and the constant group delay without using any iterative optimization. Also, we present a design method with specified maximum pole radius to achieve robust stability. Finally, design examples are presented to illustrate the effectiveness of the proposed method by designing a high-pass and low-pass IIR digital filter.

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Peak-Error-Constrained Sparse FIR Filter Design Using Iterative SOCP

Cited by 57 publications

References 27 publications

A Novel Design of Sparse FIR Multiple Notch Filters with Tunable Notch Frequencies

A Novel Design of Sparse FIR Multiple Notch Filters with Tunable Notch Frequencies

The Design of Linear-Phase FIR Multiple-Notch Filters with Variable Notch Frequencies

A System Identification Based Approach for Design of IIR Digital Filters with Robust Stability

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