Improved Real-time Denoising Method Based on Lifting Wavelet Transform

Liu, Zhaohua; Mi, Yang; Mao, Yuliang

doi:10.2478/msr-2014-0020

Cited by 15 publications

(6 citation statements)

References 11 publications

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“…In addition, the more important drawback is that soft and hard threshold functions do not have continuous derivatives. Various improvements had been proposed by exploring new threshold functions [1,[10][11][12][13][14][15][16][17], but the nonnegative garrotelike functions [10][11][12][13][14] are still not differentiable. Zhang [1,15], Nasri and Nezamabadi-pour [16], and Wu et al [17], respectively, proposed a series of threshold functions with adjustable parameters.…”

Section: Introductionmentioning

confidence: 99%

Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function

Gong¹,

Yang²,

Wang³

et al. 2017

Mathematical Problems in Engineering

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Unlike inflexible structure of soft and hard threshold function, a unified linear matrix form with flexible structure for threshold function is proposed. Based on the unified linear flexible structure threshold function, both supervised and unsupervised subband adaptive denoising frameworks are established. To determine flexible coefficients, a direct mean-square error (MSE) minimization is conducted in supervised denoising while Stein’s unbiased risk estimate as a MSE estimate is minimized in unsupervised denoising. The SURE rule requires no hypotheses or a priori knowledge about clean signals. Furthermore, we discuss conditions to obtain optimal coefficients for both supervised and unsupervised subband adaptive denoising frameworks. Applying an Odd-Term Reserving Polynomial (OTRP) function as concrete threshold function, simulations for polynomial order, denoising performance, and noise effect are conducted. Proper polynomial order and noise effect are analyzed. Both proposed methods are compared with soft and hard based denoising technologies—VisuShrink, SureShrink, MiniMaxShrink, and BayesShrink—in denoising performance simulation. Results show that the proposed approaches perform better in both MSE and signal-to-noise ratio (SNR) sense.

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Section: Introductionmentioning

confidence: 99%

Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function

Gong¹,

Yang²,

Wang³

et al. 2017

Mathematical Problems in Engineering

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“…If Ω is composed of A1, A2, · · · , An, then P (B) = P (A1) P (B |A1 ) + · · · + P (An) P (B |An ) (18) where B is an arbitrary event, and P (B |Aj ) is the conditional probability of B given Aj.…”

Section: Total Probability Theoremmentioning

confidence: 99%

Assessment of Power Quality Based on D-S Evidence Theory

Dou

Gui

Yang

et al. 2014

Int. J. Autom. Comput.

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Technological advancement of measurement systems has enhanced the accuracy of power quality assessment by using a combination of measured information. This paper proposes a novel approach for estimating power quality based on information fusion technique of Dempster-Shafer (D-S) evidence theory. First, in order to accurately extract transient features regarding power quality indexes, wavelet packet transform and lifting wavelet transform are proposed to detect various disturbance signals measurement. By using many kinds of transformed transient indexes and steady state indexes, a novel reliability distribution function is constructed, and synthesized assessment index of power quality is drafted based on information fusion technique of D-S evidence theory. Finally, the simulation results prove that D-S evidence theory is a more effective means for evaluating the power quality.

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“…As soon as the minimum length is reached, the first window initiates and online denoising begins. Subsequently, the window moves ahead step by step with the width fixed [18,19]. Fig.3 shows the designed of the system block diagram.…”

Section: Fig 2: Db7 Waveletmentioning

confidence: 99%

Online Wavelet Denoising for a Quarter Car Model

Postalcioglu¹

2018

IJCA

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Noise impact cannot be ignored in control system. In online systems when the received data by sensor contains noise, may cause to a problem. Linear position sensor can be widely used to control of body motion in different types of suspension system. Sensor's resolution, accuracy and stability depend on its electronics design. For this purpose, in this paper an online wavelet denoising has been studied for a quarter car model. Vibrations due to the unit step input are controlled with PID controller. If the sensor contains noise, controller performance will be poor. Online wavelet denoising is used to eliminate the noise. Simulation results show that when the system has online wavelet denoising, controller gives better results and system is not affected by the noise. As a result, this type of control strategy can be applied to the semi-active suspension systems to improve driver comfort.

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Improved Real-time Denoising Method Based on Lifting Wavelet Transform

Cited by 15 publications

References 11 publications

Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function

Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function

Assessment of Power Quality Based on D-S Evidence Theory

Online Wavelet Denoising for a Quarter Car Model

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