Minimax phase error design of allpass variable fractional-delay digital filters by iterative weighted least-squares method

Shyu, Jong-Jy; Pei, Soo‐Chang; Chan, Cheng-Han

doi:10.1016/j.sigpro.2009.03.021

Cited by 34 publications

(35 citation statements)

References 23 publications

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“…To get a higher-accuracy and higher-fidelity DEM, it is necessary to do some experiments recovered by different parameter estimation algorithms, and make comparisons about the results. Addressing the problem of distortion, the LS is one of the most widely used algorithms (Shyu, 2009;Wang, Qiu, & Cheng, 2011), whose principle is that minimizing the sum of squared residuals (shown in Figure 2) of the differences between the distorted values and recovered values to get the parameters of model. However, the LS cannot avoid abnormal data (DEM often presents in some mutations of elevation), the RANSAC is taken to compare with the LS, for it can reduce the interference of anomalous data and is widely used to improve the data accuracy (Schnabel, Wahl, & Klein, 2007;Raguram, 2008;Zhou, Zhu, & Li, 2011).…”

Section: Problem Analysismentioning

confidence: 99%

A Method of Recovering Distorted DEM of Regular Terrain

2017

Revista Tecnica De La Facultad De Ingenieria Universidad Del Zu

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The distortion often occurs in digital elevation model (DEM) depicting terrain, and there is no good strategy to recover distorted DEM. It is necessary to make a recovery for a high-accuracy and high-fidelity DEM. In this paper, a method is proposed to recover the DEM which is used to depict regular terrain by taking a flat terrain object as an example. According to the terrain feature of flat terrain, it should be a plane of DEM, and the equation of plane can be solved by parameter estimation algorithms. This research selects the Least-Squares method (LS) and the Random Sample Consensus algorithm (RANSAC) to estimate the parameters of equation. Based on the plane equation, the recovered DEM can be obtained. The result shows that the recovery method is effective and feasible, and the recovered DEM not only has a higher accuracy, but can reflect terrain feature fully and exactly. With a large quantity of grid points, the recovering capacities of two algorithms are similar. However, compared with the LS, the RANSAC can adapt to the mutations of elevation with a better robustness.

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Section: Problem Analysismentioning

confidence: 99%

A Method of Recovering Distorted DEM of Regular Terrain

2017

Revista Tecnica De La Facultad De Ingenieria Universidad Del Zu

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“…That is, a recursive digital filter may become unstable if the stability conditions are violated. Such a stabilityguarantee issue is more important in designing and implementing a variable-coefficient recursive digital filter (variable recursive filter) whose frequency-domain response is constantly tuned [1][2][3][4][5][6][7][8][9]. The reason is that the denominator coefficients of a variable recursive filter are frequently changed in the filtering process, and such coefficient-value changes may cause instability.…”

Section: Introductionmentioning

confidence: 99%

“…The reason is that the denominator coefficients of a variable recursive filter are frequently changed in the filtering process, and such coefficient-value changes may cause instability. In [1][2][3][4][5], the variable recursive filters are designed to have variable-magnitude responses, while those in [6][7][8][9] have variable fractional-delay responses. The design method in [1] cannot theoretically ensure the stability of the designed variable recursive filter, and the tuning process may lead to an unstable variable filter.…”

Section: Introductionmentioning

confidence: 99%

Stability trapezoid and stability-margin analysis for the second-order recursive digital filter

Deng

2016

Signal Processing

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“…Iterative reweighted least squares (IRLS) algorithms solve the filter design problem by solving a series of WLS subproblems transformed from the original one, and have been verified to be very efficient and flexible for designing various digital filters [5,[7][8][9][10][11][12][13][14][15][16]. The basic IRLS algorithm was first developed by Lawson [17] to achieve a minimax approximation.…”

Section: Introductionmentioning

confidence: 99%

A new iterative reweighted least squares algorithm for the design of FIR filters

Zhao

Lai

2013

2013 9th International Conference on Information, Communications &Amp; Signal Processing

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It is known that iterative reweighted least squares (IRLS) algorithms are efficient techniques for the design of digital filters. The main computational load in IRLS algorithms is to solve a series of weighted least squares (WLS) subproblems, which usually needs the time-consuming evaluation of matrix inversion. This paper presents a new and very efficient IRLS algorithm, in which a simple iterative procedure is developed for solving those WLS subproblems. It is verified that the iterative procedure is guaranteed to converge and is computationally more efficient than using matrix inversion. Thus, the design efficiency is improved greatly, especially for high-order filters. Design examples and comparisons to some existing algorithms are given to show the excellent performance of the proposed algorithm.

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Minimax phase error design of allpass variable fractional-delay digital filters by iterative weighted least-squares method

Cited by 34 publications

References 23 publications

A Method of Recovering Distorted DEM of Regular Terrain

A Method of Recovering Distorted DEM of Regular Terrain

Stability trapezoid and stability-margin analysis for the second-order recursive digital filter

A new iterative reweighted least squares algorithm for the design of FIR filters

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