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Journal articles on the topic 'Wavelet moment'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

SUN, YANKUI. "LIFTING CONSTRUCTION OF SPLINE DYADIC WAVELET FILTERS WITH ANY NUMBER OF VANISHING MOMENTS." International Journal of Wavelets, Multiresolution and Information Processing 07, no. 05 (2009): 693–710. http://dx.doi.org/10.1142/s0219691309003148.

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The dyadic lifting schemes, which generalize Sweldens lifting schemes, have been applied to design dyadic wavelet with higher number of vanishing moments. But the existing dyadic lifting methods cannot give the free parameters (i.e. lifting factors) explicitly under vanishing moment constraints, and the exact vanishing moments of the lifted wavelet is unknown a priori. This paper provides a solution of these problems for spline dyadic wavelets. It proposes a novel constructive method for lifting constructing spline dyadic wavelets with desirable numbers of vanishing moments. This new lifting c

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2

Kathuria, Leena, Shashank Goel, and Nikhil Khanna. "Fourier–Boas-Like Wavelets and Their Vanishing Moments." Journal of Mathematics 2021 (March 6, 2021): 1–7. http://dx.doi.org/10.1155/2021/6619551.

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In this paper, we propose Fourier–Boas-Like wavelets and obtain sufficient conditions for their higher vanishing moments. A sufficient condition is given to obtain moment formula for such wavelets. Some properties of Fourier–Boas-Like wavelets associated with Riesz projectors are also given. Finally, we formulate a variation diminishing wavelet associated with a Fourier–Boas-Like wavelet.

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3

Gong, Jing. "Influence of wavelet characteristics on single-phase grounding fault line selection." IOP Conference Series: Earth and Environmental Science 983, no. 1 (2022): 012015. http://dx.doi.org/10.1088/1755-1315/983/1/012015.

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Abstract It is difficult to select the fault line in distribution network because of the small single-phase grounding fault current. Wavelet transform is especially suitable for fault transient analysis because of its unique time-frequency localization performance. However, the characteristics of different wavelets have a direct impact on the line selection results. Improper selection of wavelets will directly lead to misjudgment. Firstly, the transient characteristics of single-phase grounding fault and the relationship between wavelet transform modulus maxima and singularity are analysed, an

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Zhu, Bin, and Wei Dong Jin. "Feature Analysis of Advanced Radar Emitter Signals Based on Continuous Wavelet Transform." Applied Mechanics and Materials 246-247 (December 2012): 1125–29. http://dx.doi.org/10.4028/www.scientific.net/amm.246-247.1125.

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For further study the recognition problem of radar emitter signals (RES), the theory of continuous wavelet transform (CWT) and gray moment are introduced into the feature extraction of RES. A new approach for RES feature extraction was proposed based on CWT and gray moment. By using the time-frequency domain characteristics of wavelet analysis and the moment-based method, the CWT coefficients of RES and the changing rules of RES gray moment were researched. The experiment results shows that the wavelet gray moments of the RES take on a rising trend along with the increase of the order, and the

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5

Li, Rui Ming, Liang Gong, and Qi Xiong. "Construction Method of Perfect Reconstruction Condition-Based Biorthogonal Wavelet." Applied Mechanics and Materials 416-417 (September 2013): 1305–8. http://dx.doi.org/10.4028/www.scientific.net/amm.416-417.1305.

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This paper proposes a general construction method of biorthogonal wavelet based on perfect reconstruction condition. With the certain filter length and vanishing moment, it can educe the biorthogonal wavelets filter coefficient by solving equations. Thereafter, this method constructs 5/3 wavelet, CDF9/7 wavelet and 9/7 wavelet with simple coefficient, which applies well to hardware, for JPEG2000.

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Xiang, Jiawei, Zhansi Jiang, and Xuefeng Chen. "A Class of Wavelet-Based Rayleigh-Euler Beam Element for Analyzing Rotating Shafts." Shock and Vibration 18, no. 3 (2011): 447–58. http://dx.doi.org/10.1155/2011/563124.

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A class of wavelet-based Rayleigh-Euler rotating beam element using B-spline wavelets on the interval (BSWI) is developed to analyze rotor-bearing system. The effects of translational and rotary inertia, torsion moment, axial displacement, cross-coupled stiffness and damping coefficients of bearings, hysteric and viscous internal damping, gyroscopic moments and bending deformation of the system are included in the computational model. In order to get a generalized formulation of wavelet-based element, each boundary node is collocated six degrees of freedom (DOFs): three translations and three

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Pathak, Ashish. "Moment asymptotic expansions of the wavelet transforms." Boletim da Sociedade Paranaense de Matemática 35, no. 1 (2017): 237. http://dx.doi.org/10.5269/bspm.v35i1.28412.

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Using distribution theory we present the moment asymptotic ex-pansion of continuous wavelet transform in dierent distribution spaces for largeand small values of dilation parameter a. We also obtain asymptotic expansionsfor certain wavelet transform.

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8

KARRAS, DIMITRIOS. "An Efficient Feature Extraction Methodology for Computer Vision Applications using Wavelet Compressed Zernike Moments." ICGST International Journal on Graphics, Vision and Image Processing 5 (September 30, 2005): 5–15. https://doi.org/10.5281/zenodo.13837686.

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Papakostas, G. A., Karras, D. A., Mertzios, B. G., & Boutalis, Y. S. (2005). An efficient feature extraction methodology for computer vision applications using wavelet compressed Zernike moments. <em>ICGST International Journal on Graphics, Vision and Image Processing, Special Issue: Wavelets and Their Applications</em>, 5-15.   An Efficient Feature Extraction Methodology for Computer Vision Applicationsusing Wavelet Compressed Zernike Moments G. A. Papakostas1, D. A. Karras2, B. G. Mertzios3 and Y. S. Boutalis1 1 Democritus University of Thrace, Department of Electr. and Comp. E

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Lashab, Mohamed, Chems-Edine Zebiri, and Fatiha Benabdelaziz. "WAVELET-BASED MOMENT METHOD AND WAVELET-BASED MOMENT METHOD AND PHYSICAL OPTICS USE ON LARGE REFLECTOR ANTENNAS." Progress In Electromagnetics Research M 2 (2008): 189–200. http://dx.doi.org/10.2528/pierm08042902.

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10

Liu, Caixia, and Li Zhang. "A Novel Denoising Algorithm Based on Wavelet and Non-Local Moment Mean Filtering." Electronics 12, no. 6 (2023): 1461. http://dx.doi.org/10.3390/electronics12061461.

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Denoising is the basis and premise of image processing and an important part of image preprocessing. Denoising can effectively improve image quality, which contributes to subsequent image processing such as image segmentation, feature extraction, and so on. In this paper, we propose a novel image denoising method based on wavelet transform and nonlocal moment mean filtering approach (NMM). The noisy image is firstly denoised by a wavelet-based soft-thresholding denoising technique and NMM is then utilized to further eliminate the rest noises. Meanwhile, the fusion of moment invariants increase

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11

Choi, Chang-Soo, Jong-Cheon Park, and Byoung-Min Jun. "A Iris Recognition Using Zernike Moment and Wavelet." Journal of the Korea Academia-Industrial cooperation Society 11, no. 11 (2010): 4568–75. http://dx.doi.org/10.5762/kais.2010.11.11.4568.

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12

Lazear, Gregory D. "Mixed‐phase wavelet estimation using fourth‐order cumulants." GEOPHYSICS 58, no. 7 (1993): 1042–51. http://dx.doi.org/10.1190/1.1443480.

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In recent years methods have been developed in the field of high‐order statistics that can reliably estimate a mixed‐phase wavelet from the noisy output of a convolutional process. These methods use high‐order covariance functions of the data called cumulants, which retain phase information and allow recovery of the wavelet. The assumption is that the reflection coefficient series is a non‐Gaussian, stationary, and statistically independent random process. The method described in this paper uses the fourth‐order cumulant of the data, and a moving‐average, noncausal parametric model for the wav

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13

Ahn, Seok Hwan, K. Y. Seong, Jin Wook Kim, and Ki Woo Nam. "Wavelet Analysis of Elastic Wave for Wall Thinned Inconel 690 Tube." Key Engineering Materials 353-358 (September 2007): 2281–84. http://dx.doi.org/10.4028/www.scientific.net/kem.353-358.2281.

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The bending moment test used by the specimens with partial and circumferential wall thinning was carried out to obtain the AE signal. The time-frequency analysis method for the investigation of the frequency characteristics of the AE signal was applied. The results of the wavelet analysis were compared with those of the bending moment test for the structural integrity of tube. The result of the frequency characteristics by applying wavelet analysis method and dropping ball test was presented similarly to those of bending moment test. It is considered that this simple method with combination of

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Zhang, Jianhua, Qiang Zhu, Fei Song, Lingchao Zhang, Juan Wang, and Changjun Liu. "Multi-Scale Edge Detection of Crack in Extra-High Arch Dam Based on Orthogonal Wavelet Construction." Traitement du Signal 39, no. 3 (2022): 977–89. http://dx.doi.org/10.18280/ts.390325.

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This paper conducts a research on the wavelet construction and application of image edge detection. Taking the image edge detection algorithm based on wavelet modulus maxima as the research subject, this paper discusses the problem of dislocation phenomenon, threshold selection, multi-scale edge fusion and evaluation criterion in the algorithm, and proposes an improved self-adaptive hierarchical threshold algorithm based on information amount and vanishing moment. From the angle of wavelet symmetry, filter composition and vanishing moment, the influence of wavelet property on image edge detect

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15

Chen, Kun Wei, Xing Guo, and Jian Guo Wu. "Gesture Recognition System Based on Wavelet Moment." Applied Mechanics and Materials 401-403 (September 2013): 1377–80. http://dx.doi.org/10.4028/www.scientific.net/amm.401-403.1377.

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Vision-based gesturerecognition is a key technique to achieve a new generation of human-computerinteraction. As few text input search system by gesture recognition isdeveloped, based on the existing gesture recognition techniques, we use thegestures which are corresponding to the Chinese letters and numbers as inputgesture and use Microsoft kinect to obtain depth image to conduct hand gesturesegmentation. First, the edge of the gesture is extracted by Canny algorithm,and then the feature is extracted based on wavelet moment. Finally the gestureletters are obtained. Achieved the text input syst

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16

Chen, Guangyi. "Wavelet-based moment invariants for pattern recognition." Optical Engineering 50, no. 7 (2011): 077205. http://dx.doi.org/10.1117/1.3597329.

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17

Gao, Junqi, Lingsi Sun, Shuxiang Zhao, and Ying Shen. "Enhanced ACFM detection performance by multi-parameter synergy analysis." Insight - Non-Destructive Testing and Condition Monitoring 62, no. 2 (2020): 81–85. http://dx.doi.org/10.1784/insi.2020.62.2.81.

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A procedure for the enhancement of alternating current field measurement (ACFM) detection performance is proposed based on a multi-parameter synergy analysis (MPSA) algorithm. Firstly, to gain the maximised ACFM signal characteristics, wavelet base property matching is adopted to choose the favourable wavelet bases. To this aim, the following six base properties should be considered: orthogonality, compact support, symmetry, discrete wavelet transform (DWT), vanishing moment and regularity. It is found that the applicable wavelet bases are Haar, Daubechies (DbN), Symlets (SymN) and Coiflets (C

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18

Selvi, Oguz. "A note on digital filtering with the second moment norm." GEOPHYSICS 62, no. 4 (1997): 1315–20. http://dx.doi.org/10.1190/1.1444233.

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The linear inverse method developed by Backus and Gilbert (1968) relates model estimates to actual earth models by use of a resolving kernel. Seismic source wavelet deconvolution can be treated within the framework of the Backus and Gilbert (1968) inverse theory as presented in Oldenburg (1981) and Treitel and Lines (1982). The model of the Backus and Gilbert theory is the ground impulse response, the mapping kernel is the source wavelet, and the resolving kernel is the convolution between the source wavelet and the shaping filter. Backus and Gilbert formalism introduces several measures for t

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19

Veneziano, D., and P. Furcolo. "Improved moment scaling estimation for multifractal signals." Nonlinear Processes in Geophysics 16, no. 6 (2009): 641–53. http://dx.doi.org/10.5194/npg-16-641-2009.

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Abstract. A fundamental problem in the analysis of multifractal processes is to estimate the scaling exponent K(q) of moments of different order q from data. Conventional estimators use the empirical moments μ^rq=⟨ | εr(τ)|q⟩ of wavelet coefficients εr(τ), where τ is location and r is resolution. For stationary measures one usually considers "wavelets of order 0" (averages), whereas for functions with multifractal increments one must use wavelets of order at least 1. One obtains K^(q) as the slope of log( μ^rq) against log(r) over a range of r. Negative moments are sensitive to measurement noi

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20

Hong, Dawei, Shushuang Man, Jean-Camille Birget, and Desmond S. Lun. "A Wavelet-Based Almost-Sure Uniform Approximation of Fractional Brownian Motion with a Parallel Algorithm." Journal of Applied Probability 51, no. 01 (2014): 1–18. http://dx.doi.org/10.1017/s0021900200010044.

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We construct a wavelet-based almost-sure uniform approximation of fractional Brownian motion (FBM) (Bt(H))_t∈[0,1]of Hurst indexH∈ (0, 1). Our results show that, by Haar wavelets which merely have one vanishing moment, an almost-sure uniform expansion of FBM forH∈ (0, 1) can be established. The convergence rate of our approximation is derived. We also describe a parallel algorithm that generates sample paths of an FBM efficiently.

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21

KUMAR, SANJAY, and DINESH K. KUMAR. "VISUAL HAND GESTURES CLASSIFICATION USING WAVELET TRANSFORM AND MOMENT BASED FEATURES." International Journal of Wavelets, Multiresolution and Information Processing 03, no. 01 (2005): 79–101. http://dx.doi.org/10.1142/s0219691305000762.

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This paper presents a novel technique for classifying human hand gestures based on stationary wavelet transform (SWT) and classification based on geometrical based moments and compares the results with the classification based on Hu-moments and wavelet approximate images. The technique uses view-based approach for representation of hand actions, and uses a cumulative image-difference technique where the time between the sequences of images is implicitly captured in the representation of action resulting in Motion History Images (MHI). These MHIs are decomposed into wavelet sub-images using SWT

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22

Ding, Liwang, and Ping Chen. "A note on the consistency of wavelet estimators in nonparametric regression model under widely orthant dependent random errors." Mathematica Slovaca 69, no. 6 (2019): 1471–84. http://dx.doi.org/10.1515/ms-2017-0323.

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Abstract In this paper, we consider the wavelet estimators of a nonparametric regression model based on widely orthant dependent random errors. The moment consistency and the completely consistency for wavelet estimators under some more mild moment conditions are investigated. The results obtained in the paper improve and extend the corresponding ones for dependent random variables. Finally, we provide a numerical simulation to verify the validity of our results.

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23

Hong, Dawei, Shushuang Man, Jean-Camille Birget, and Desmond S. Lun. "A Wavelet-Based Almost-Sure Uniform Approximation of Fractional Brownian Motion with a Parallel Algorithm." Journal of Applied Probability 51, no. 1 (2014): 1–18. http://dx.doi.org/10.1239/jap/1395771410.

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We construct a wavelet-based almost-sure uniform approximation of fractional Brownian motion (FBM) (Bt(H))_t∈[0,1] of Hurst index H ∈ (0, 1). Our results show that, by Haar wavelets which merely have one vanishing moment, an almost-sure uniform expansion of FBM for H ∈ (0, 1) can be established. The convergence rate of our approximation is derived. We also describe a parallel algorithm that generates sample paths of an FBM efficiently.

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24

Xuan, Jian Ping, Zeng Bing Xu, Bo Wu, and Tie Lin Shi. "Wavelet Grey Moment Vector and Hidden Markov Model Based Fault Diagnosis for Ball Bearing." Advanced Materials Research 346 (September 2011): 210–15. http://dx.doi.org/10.4028/www.scientific.net/amr.346.210.

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The paper introduces a new approach to detect the fault of bearing based on wavelet grey moment vector and hidden Markov modeling (HMM). Because of non-stationary characteristics of vibration signals of faulty bearings, we propose a new method to extract the wavelet grey moment vectors from these signals. The grey moment vectors are used as feature parameters to train HMMs to establish the database. Fault modes of bearings can be identified by select the HMM with the highest probability. The experimental results show that the proposed approach is effective and accurate to detect the faulty bea

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Li, Na. "Construction of a Class of Nonseparable Compactly Supported Wavelets with Special Dilation Matrix in L²(R⁴)." Advanced Materials Research 393-395 (November 2011): 659–62. http://dx.doi.org/10.4028/www.scientific.net/amr.393-395.659.

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In this paper, a novel method to construct the compactly supported wavelet under a mild condition. The constructed wavelet satisfies the vanishing moment condition which is originated from the symbols of the scaling function.

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26

Deng, H., and H. Ling. "Moment matrix sparsification using adaptive wavelet packet transform." Electronics Letters 33, no. 13 (1997): 1127. http://dx.doi.org/10.1049/el:19970782.

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27

Xiao, Jinyou, Johannes Tausch, and Lihua Wen. "Approximate moment matrix decomposition in wavelet Galerkin BEM." Computer Methods in Applied Mechanics and Engineering 197, no. 45-48 (2008): 4000–4006. http://dx.doi.org/10.1016/j.cma.2008.03.015.

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28

Li, Lan. "Design of High Dimensional Nonseparable Compactly Supported Wavelets with Special Dilation Matrix." Advanced Materials Research 542-543 (June 2012): 547–50. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.547.

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In this paper, a new method to construct the compactly supported M- wavelet under a mild condition are given. The constructed wavelet satisfies the vanishing moment condition which is originated from the symbols of the scaling function.

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29

Gao, Jing, and Yao-Lin Jiang. "A periodic wavelet method for the second kind of the logarithmic integral equation." Bulletin of the Australian Mathematical Society 76, no. 3 (2007): 321–36. http://dx.doi.org/10.1017/s0004972700039721.

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A periodic wavelet Galerkin method is presented in this paper to solve a weakly singular integral equations with emphasis on the second kind of Fredholm integral equations. The kernel function, which includes of a smooth part and a log weakly singular part, is discretised by the periodic Daubechies wavelets. The wavelet compression strategy and the hyperbolic cross approximation technique are used to approximate the weakly singular and smooth kernel functions. Meanwhile, the sparse matrix of systems can be correspondingly obtained. The bi-conjugate gradient iterative method is used to solve th

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30

Meethongjan, Khitikun, Mohamad Dzulkifli, Amjad Rehman, Ayman Altameem, and Tanzila Saba. "An Intelligent Fused Approach for Face Recognition." Journal of Intelligent Systems 22, no. 2 (2013): 197–212. http://dx.doi.org/10.1515/jisys-2013-0010.

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AbstractFace detection plays important roles in many applications such as human–computer interaction, security and surveillance, face recognition, etc. This article presents an intelligent enhanced fused approach for face recognition based on the Voronoi diagram (VD) and wavelet moment invariants. Discrete wavelet transform and moment invariants are used for feature extraction of the facial face. Finally, VD and the dual tessellation (Delaunay triangulation, DT) are used to locate and detect original face images. Face recognition results based on this new fusion are promising in the state of t

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Zhang, Yong Hong, L. H. Wang, and De Jin Hu. "Key Technologies of Image Measurement for Curve Accurate Grinding." Key Engineering Materials 329 (January 2007): 533–38. http://dx.doi.org/10.4028/www.scientific.net/kem.329.533.

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Image analysis was used to evaluate the curve grinding process. The measurement system organization and its principle of operation were introduced. Some key technologies that influence the system precision were also studied in details. Real-time image of work piece and wheel grinding can be gathered while using CCD camera. For image de-noising, a kind of wavelet threshold function was presented to calculate the new wavelet coefficients. Local threshold algorithm was used to compute different scale threshold, another threshold is suggested when MSE is minimum. Image signals are reconstructed th

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Mostarac, Petar, Roman Malarić, Katarina Mostarac, and Marko Jurčević. "Noise Reduction of Power Quality Measurements with Time-Frequency Depth Analysis." Energies 12, no. 6 (2019): 1052. http://dx.doi.org/10.3390/en12061052.

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This paper presents the noise reduction of power quality measurement with time-frequency (T-F) depth analysis. Noise reduction is achieved with wavelet transformation by decomposition, thresholding and lossless reconstruction of signal. Three main problems with T-F noise reduction with wavelet transformation are: defining thresholding levels, level of decomposition and number of wavelet vanishing moment. In this analysis decomposition level and number of vanishing moments are defined via simulation for pure sinusoid signal, these values are used for signals with perturbations and they provide

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Zhou, Jin Jin, and Wei Xing Zhu. "Gesture Recognition of Pigs Based on Wavelet Moment and Probabilistic Neural Network." Applied Mechanics and Materials 687-691 (November 2014): 3691–94. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.3691.

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For real-time monitoring the behavior of pigs in piggery, the method that combined the advantages of wavelet multi-scale analysis with invariant moments is proposed. Firstly, the original image is pre-processed by using ant colony algorithm to extract object contour. Then the target contour edge growth method and binary morphology are used, and the outlines of pigs are extracted by canny operator. Wavelet moment was used to get the global features of an image and increase the structural details of the image feature description. Finally, the neural network is applied to identify four behaviors

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34

Khare, Manish, and Ashish Khare. "TRACKING OF MULTIPLE HUMAN OBJECTS USING COMBINATION OF DAUBECHIES COMPLEX WAVELET TRANSFORM AND ZERNIKE MOMENT." ICTACT Journal on Image and Video Processing 11, no. 1 (2020): 2232–44. https://doi.org/10.21917/ijivp.2020.0320.

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The goal of multi object tracking is to find location of the target objects in number of consecutive frames of a video. Tracking of multiple human objects in a scene is one of the challenging problems in computer vision applications due to illumination variation, object occlusion, abrupt motion etc. This paper introduces a new method for multiple human object tracking by exploiting the properties of Daubechies complex wavelet transform and Zernike moment. The proposed method uses combination of Daubechies complex wavelet transform and Zernike moment as a feature of objects. The motivation behi

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Sun, Zeng Shou, Ke Ju Fan, Xu Guang Yin, and Peng Jie Han. "The Research of Civil Structural Damage Identification Based on Lifting Wavelet Entropy Index." Advanced Materials Research 291-294 (July 2011): 2041–48. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.2041.

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The failure of civil engineering structure will lead to heavy losses. So, identifying structural damage is necessary as early as possible. The excellent localization performance of lifting wavelet transform will facilitate significantly damage diagnosis. On the base of wavelet energy distribution of structural acceleration response, taking advantage of characteristics of lifting wavelet and entropy, the structural damage identification method based on lifting wavelet entropy is proposed in this paper. And the lifting wavelet time entropy index and the relative lifting wavelet entropy index are

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Handy, C. R., R. Murenzi, K. Bouyoucef, and H. A. Brooks. "Moment-wavelet quantization and (complex) multiple turning point contributions." Journal of Physics A: Mathematical and General 33, no. 10 (2000): 2151–77. http://dx.doi.org/10.1088/0305-4470/33/10/314.

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Führ, Hartmut. "Vanishing moment conditions for wavelet atoms in higher dimensions." Advances in Computational Mathematics 42, no. 1 (2015): 127–53. http://dx.doi.org/10.1007/s10444-015-9414-3.

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Huang, Shu-ling, Yong-jie Pang, Bo Wang, and Lei Wan. "Wavelet moment invariants extraction of underwater laser vision image." Journal of Shanghai Jiaotong University (Science) 18, no. 6 (2013): 712–18. http://dx.doi.org/10.1007/s12204-013-1454-6.

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Guerrier, Stephane, Juan Jurado, Mehran Khaghani, et al. "Wavelet-Based Moment-Matching Techniques for Inertial Sensor Calibration." IEEE Transactions on Instrumentation and Measurement 69, no. 10 (2020): 7542–51. http://dx.doi.org/10.1109/tim.2020.2984820.

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Zhang, Feng, Shang-qian Liu, Da-bao Wang, and Wei Guan. "Aircraft recognition in infrared image using wavelet moment invariants." Image and Vision Computing 27, no. 4 (2009): 313–18. http://dx.doi.org/10.1016/j.imavis.2008.08.007.

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Kim, Hyeongdong, and Hao Ling. "A fast multiresolution moment-method algorithm using wavelet concepts." Microwave and Optical Technology Letters 10, no. 6 (1995): 317–19. http://dx.doi.org/10.1002/mop.4650100604.

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Ergu, Yared Abera. "Medical Image Mixed Denoise using Discrete Multi Wavlet Transform Novel Threshold Method." International Journal of Technology Information and Computer (TIJOTIC) 1, no. 1 (2020): 16–28. https://doi.org/10.5281/zenodo.3888529.

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Generally, most of the<strong> </strong>images are corrupted by noise which is solved by denoising techniques in the image processing.  For that single thresholding techniques are used which removes the additive random noise. The Gaussian -Multi Wavelet technique is utilized to denoising the Gaussian noise present in the mammogram image which is an efficient method due to the capability to acquire the signal energies in few transforms value. In order to enhance and the noise present in the digital mammographics image, the novel Multi Wavelet techniques are used in this paper.  In the

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Li, Xiao Feng, Yun Xiao Fu, and Li Min Jia. "Fault Diagnosis of Railway Axlebox Bearing Based on Wavelet Packet and Neural Network." Applied Mechanics and Materials 226-228 (November 2012): 749–55. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.749.

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A real time and effective axlebox bearing fault diagnostic method is significant in the condition-based maintenance. In the axlebox bearing fault diagnostic system, fault features extraction and fault patterns classification are two important aspects to identify whether a axlebox bearing is failure or not. This paper presents a method of axlebox bearing fault diagnosis based on wavelet packet decomposition and BP neural network. First decompose the vibration signal into a finite number of coefficients by wavelet packet decomposition. Then calculate energy moment of each coefficient and take th

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Panahi Boroujeni, Minoo, Seyed Alireza Zareei, Mohammad Sadegh Birzhandi, and Mohammad Mahdi Zafarani. "Development of Seismic Fragility Functions for Reinforced Concrete Buildings Using Damage-Sensitive Features Based on Wavelet Theory." Structural Control and Health Monitoring 2024 (May 11, 2024): 1–22. http://dx.doi.org/10.1155/2024/8754191.

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In this study, wavelet-based damage-sensitive features are employed to derive the seismic fragility functions/curves for reinforced concrete moment-resisting frames. Two different wavelet transform functions, namely, Bior3.3 and Morlet mother wavelet families, were applied to absolute acceleration time histories of building frames to extract the wavelet-based and refined wavelet-based damage-sensitive features (i.e., DSF and rDSF). The accuracy of seismic assessments and certainty in predicting structural behavior strongly depend on the specific optimal intensity measures selected, reliability

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Bouri, Elie, Ladislav Kristoufek, and Nehme Azoury. "Bitcoin and S&P500: Co-movements of high-order moments in the time-frequency domain." PLOS ONE 17, no. 11 (2022): e0277924. http://dx.doi.org/10.1371/journal.pone.0277924.

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Interactions between stock and cryptocurrency markets have experienced shifts and changes in their dynamics. In this paper, we study the connection between S&P500 and Bitcoin in higher-order moments, specifically up to the fourth conditional moment, utilizing the time-scale perspective of the wavelet coherence analysis. Using data from 19 August 2011 to 14 January 2022, the results show that the co-movement between Bitcoin and S&P500 is moment-dependent and varies across time and frequency. There is very weak or even non-existent connection between the two markets before 2018. Starting

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Eubanks, David A., Patrick J. van Fleet, and Jianzhong Wang. "Moment computation in shift invariant spaces." Journal of Applied Mathematics and Stochastic Analysis 11, no. 4 (1998): 465–79. http://dx.doi.org/10.1155/s1048953398000380.

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An algorithm is given for the computation of moments of f∈S, where S is either a principal h-shift invariant space or S is a finitely generated h-shift invariant space. An error estimate for the rate of convergence of our scheme is also presented. In so doing, we obtain a result for computing inner products in these spaces. As corollaries, we derive Marsden-type identities for principal h-shift invariant spaces and finitely generated h-shift invariant spaces. Applications to wavelet/multiwavelet spaces are presented.

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Li, Chun-Feng, and Christopher Liner. "Wavelet-based detection of singularities in acoustic impedances from surface seismic reflection data." GEOPHYSICS 73, no. 1 (2008): V1—V9. http://dx.doi.org/10.1190/1.2795396.

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Although the passage of singularity information from acoustic impedance to seismic traces is now well understood, it remains unanswered how routine seismic processing, mode conversions, and multiple reflections can affect the singularity analysis of surface seismic data. We make theoretical investigations on the transition of singularity behaviors from acoustic impedances to surface seismic data. We also perform numerical, wavelet-based singularity analysis on an elastic synthetic data set that is processed through routine seismic processing steps (such as stacking and migration) and that cont

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Handy, C. R., and R. Murenzi. "Moment-wavelet quantization: a first principles analysis of quantum mechanics through continuous wavelet transform theory." Physics Letters A 248, no. 1 (1998): 7–15. http://dx.doi.org/10.1016/s0375-9601(98)00645-8.

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Zhang, Zheng Bao, and Chao Jia. "Digital Image Zero-Watermarking Algorithm Based on Improved Wavelet Moment." Applied Mechanics and Materials 347-350 (August 2013): 3232–36. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3232.

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Lots of anti-RST attacks watermarking algorithms have been proposed, but few solutions for local geometric attacks, in this paper it proposed a new algorithm combined with the the Wavelet Moment for an anti-geometric attacks. Since wavelet moment was proposed, it is widely used in the field of computer vision, image processing, but the large amount of computation must be improved to be applied to digital watermarking technology so that it can adapt to the real-time detection of digital watermarking. By image rotation, scaling, translation, shear, local distortions, filtering attack operations

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Liu, Jun, Lin Li, and Qing Tao Long. "Power System Fault Diagnosis Based on Wavelet Transform and Neural Networks." Applied Mechanics and Materials 705 (December 2014): 255–58. http://dx.doi.org/10.4028/www.scientific.net/amm.705.255.

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Using the principle of wavelet transform in the aspect of signal singularity detection analyzes and detects the electric power system fault signal. Then we extract signal feature near the fault moment and sent the feature vectors into the neural network. The simulation results fully prove the effectiveness and superiority of combining wavelet transform and neural network in electric power system fault recognition.

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