Linear phase FIR differentiator design based on maximum signal-to-noise ratio criterion

Tseng, Chien‐Cheng; Lee, Su-Ling

doi:10.1016/j.sigpro.2005.06.004

Cited by 8 publications

(5 citation statements)

References 20 publications

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“…The method is then used to design first order low pass differentiators, we have discussed different options available separately. It is illustrated that the designed differentiator has less transition width and overshoot in frequency response, as compared to other techniques, [5] and [6]. The problem of fractional order case of low pass differentiator could also be solved by using minmax technique discussed in the paper.…”

Section: Discussionmentioning

confidence: 96%

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FIR Linear Phase Fractional Order Digital Differentiator Design using Convex Optimization

Singh¹,

Singh²

2014

IJAIS

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In this paper, design of linear phase FIR digital differentiators is investigated using convex optimization. The problem of differentiator design is first described in terms of convex optimization with different optimization variables' options, taken one at a time. The method is then used to design first order low pass differentiators and results are compared with Salesnick's technique and Parks McClellan algorithm. The designed FIR low pass differentiator has improvement in transition width and flexibility to optimize different parameters. The concept of low pass differentiation is further generalized to fractional order differentiators. Fractional order differentiators are designed by using minmax technique on mean square error. Design examples demonstrate easy design procedure and flexibility in the process as well as improvement over existing fractional order differentiators in terms of mean square error in passband. Finally, fractional order differentiators are designed and used for texture enhancement of color images. Better texture enhancement than existing filtering approaches is established based on average gradient and entropy values. General TermsFIR Filter, Fractional order differentiator, Low pass differentiator, Full band differentiator, Image Enhancement.

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Section: Discussionmentioning

confidence: 96%

“…Higher order differentiation is used in biomedical signal processing, radar and sonar, image processing, velocity and acceleration measurement etc. [5]. Low pass digital differentiators are used to avoid unwanted amplification of noise, as in case of full band ones [6].…”

Section: Introduction Fir Filters Are Characterized By Following Equamentioning

confidence: 99%

FIR Linear Phase Fractional Order Digital Differentiator Design using Convex Optimization

Singh¹,

Singh²

2014

IJAIS

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“…As can be seen from the mathematical definitions of the four geometric properties of interest, the next necessary step is the differentiation of r, realized thanks to a simple linear phase FIR differentiator filter. Instead of a full-band differentiator, a partial-band differentiator adapted to the selected frequency f 0 is used in order to avoid amplifying possible residual high frequency components and maximize the signal-to-noise ratio (SNR) at the output of each differentiator [16]. Since r needs to be differentiated three times, the same differentiator filter is applied three times consecutively to r. The use of the frequency-selective and differentiator FIR filters means that there are signal delays that need to be managed after each application of a filter to synchronize the signals.…”

Section: General Structurementioning

confidence: 99%

Estimation of geometric properties of three-component signals for system monitoring

Granjon

Phua

2017

Mechanical Systems and Signal Processing

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International audienceMost methods for condition monitoring are based on the analysis and characterization of physical quantities that are three-dimensional in nature. Plotted in a three-dimensional Euclidian space as a function of time, such quantities follow a trajectory whose geometric characteristics are representative of the state of the monitored system. Usual condition monitoring techniques often study the measured quantities component by component, without taking into account their three-dimensional nature and the geometric properties of their tra-jectory. A significant part of the information is thus ignored. This article details a method dedicated to the analysis and processing of three-component quantities, capable of highlighting the special geometric features of such data and providing complementary information for condition monitoring. The proposed method is applied to two experimental cases: bearing fault monitoring in rotating machines, and voltage dips monitoring in three-phase power networks. In this two cases, the obtained results are promising and show that the estimated geometric indicators lead to complementary information that can be useful for condition monitoring

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“…While the classical windowing method is very simple and reliable, the designs it produces are generally inferior to those produced by algorithms that employ some optimization criteria [13] . In this section, a novel iterative algorithm for optimal design of FIR digital filters based on the windowing method is presented, which is especially suitable for designing non-frequency-selective filters.…”

Section: An Iterative Algorithm For the Optimal Designmentioning

confidence: 99%

An iterative algorithm for optimal design of non-frequency-selective FIR digital filters

Tian

Duan

Sun

et al. 2008

J. Electron.(China)

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This paper proposes a novel iterative algorithm for optimal design of non-frequency-selective Finite Impulse Response (FIR) digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter, the key idea of the algorithm is minimizing the approximation error by successively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure, the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably, the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.

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Linear phase FIR differentiator design based on maximum signal-to-noise ratio criterion

Cited by 8 publications

References 20 publications

FIR Linear Phase Fractional Order Digital Differentiator Design using Convex Optimization

FIR Linear Phase Fractional Order Digital Differentiator Design using Convex Optimization

Estimation of geometric properties of three-component signals for system monitoring

An iterative algorithm for optimal design of non-frequency-selective FIR digital filters

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