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Journal articles on the topic 'Wavelet technique'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Tran, Hai, and Hirotsugu Inoue. "IMPACT FORCE RECONSTRUCTION USING WAVELET DECONVOLUTION TECHNIQUE." ASEAN Engineering Journal 8, no. 1 (2018): 53–66. http://dx.doi.org/10.11113/aej.v8.15498.

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Reconstruction or deconvolution of impact force history from corresponding impact responses such as strain, acceleration, and displacement has been considered as a useful indirect method for measuring the impact force. However, due to the ill-posed nature of deconvolution problem, impact force is often inaccurately and unstably reconstructed. This paper introduces and applies the deconvolution technique using wavelets as a robust method for reconstructing impact force with the advantageous properties of wavelets. First, an analytical process of impact force reconstruction by using the wavelet

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Tejas, Kishor Patil, and Ajeet B. Bhane Prof. "DETECTION OF CRACKS IN SIMPLY SUPPORTED BEAM BY USING VARIOUS TECHNIQUES: A REVIEW." International Journal of Research – Granthaalayah 3, no. 12 (2017): 129–32. https://doi.org/10.5281/zenodo.848956.

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In this review work the crack detection procedure by using vibration and wavelet technique is discussed. Crack converts the linear problem to nonlinear problem and affects the natural frequency. So in this paper we discussed the various methods to find out cracks on beams like destructive testing and non-destructive testing. Wavelet technique is mathematical method alternative to the non-destructive testing like fast fourier transform and is also provides good result compared to other methods. As in this the wavelets are developed and it is solved by various types like mother wavelet technique

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Enesi, Indrit, Miranda Harizaj, and Betim Çiço. "Implementing Fusion Technique Using Biorthogonal Dwt to Increase the Number of Minutiae in Fingerprint Images." Journal of Sensors 2022 (May 24, 2022): 1–13. http://dx.doi.org/10.1155/2022/3502463.

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Biometric devices identify persons based on the minutiae extracted from fingerprint images. Image quality is very important in this process. Usually, fingerprint images have low quality and in many cases they are obtained in various positions. The paper focuses on increasing minutiae detected number by fusing two fingerprint images obtained in various positions. Biorthogonal wavelets have advantages compared to orthogonal wavelets. Fusion is performed in wavelet domain by implementing biorthogonal wavelet. Terminations and bifurcations are extracted from the original and fused images using lic

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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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Ilango, S. Sudhakar, and V. Seenivasagam. "Wavelet Based Image Compression Using Soft Computing Techniques." Applied Mechanics and Materials 573 (June 2014): 477–82. http://dx.doi.org/10.4028/www.scientific.net/amm.573.477.

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The Wavelet Transform is a multi-resolution transform, that is, it allows a form of time–frequency analysis (or translation–scale in wavelet speak). When using the Fourier transform the result is a very precise analysis of the frequencies contained in the signal, but no information on when those frequencies occurred. The wavelet based image compression algorithms are used widely compared with other conventional compression algorithms. The wavelet coding based on the coefficient selection and sub band level. In this paper we have used two wavelets such as spherical and geometric wavelets. The s

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Patil, TejasKishor, and Ajeet B. Bhane. "DETECTION OF CRACKS IN SIMPLY SUPPORTED BEAM BY USING VARIOUS TECHNIQUES: A REVIEW." International Journal of Research -GRANTHAALAYAH 3, no. 12 (2015): 129–32. http://dx.doi.org/10.29121/granthaalayah.v3.i12.2015.2897.

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In this review work the crack detection procedure by using vibration and wavelet technique is discussed. Crack converts the linear problem to nonlinear problem and affects the natural frequency. So in this paper we discussed the various methods to find out cracks on beams like destructive testing and non-destructive testing. Wavelet technique is mathematical method alternative to the non-destructive testing like fast fourier transform and is also provides good result compared to other methods. As in this the wavelets are developed and it is solved by various types like mother wavelet technique

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TANAKA, NOBUATSU. "A SIMPLE BUT EFFICIENT PRECONDITIONING FOR CONJUGATE GRADIENT POISSON SOLVER USING HAAR WAVELET." International Journal of Wavelets, Multiresolution and Information Processing 04, no. 02 (2006): 273–84. http://dx.doi.org/10.1142/s0219691306001233.

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This paper describes a wavelet-based preconditioning technique for conjugate gradient method for linear systems derived from the Poisson equation. The linear systems solved with a conventional iterative matrix solver resulted in a marked increase in computing time with respect to an increase in grid points. Use of our wavelet-based technique leads to a matrix with a bounded condition number so that computing time is reduced significantly. In this study, one of the simplest wavelets, the Haar wavelet, is used for the purpose of developing a simple but efficient preconditioning algorithm. Simple

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Raath, Kim C., Katherine B. Ensor, Alena Crivello, and David W. Scott. "Denoising Non-Stationary Signals via Dynamic Multivariate Complex Wavelet Thresholding." Entropy 25, no. 11 (2023): 1546. http://dx.doi.org/10.3390/e25111546.

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Over the past few years, we have seen an increased need to analyze the dynamically changing behaviors of economic and financial time series. These needs have led to significant demand for methods that denoise non-stationary time series across time and for specific investment horizons (scales) and localized windows (blocks) of time. Wavelets have long been known to decompose non-stationary time series into their different components or scale pieces. Recent methods satisfying this demand first decompose the non-stationary time series using wavelet techniques and then apply a thresholding method

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Vivek, Suyash Narayan Mishra, and Manoj Kumar. "TAYLOR WAVELET APPROACH FOR THE SOLUTION OF THE FREDHOLM INTEGRO-DIFFERENTIAL EQUATION OF THE SECOND KIND." jnanabha 53, no. 02 (2023): 273–86. http://dx.doi.org/10.58250/jnanabha.2023.53234.

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A Taylor wavelet technique is used to obtain the approximate solution of the Fredholm integro-differential equations (IDEs) of the second kind. Taylor wavelet method is based on an estimate of the unknown function involved in a given IDEs using the Taylor wavelet basis. The simplicity of the technique is a highly striking feature for the estimate of the unknown function. The applicability of the technique on various numerical problems shows the preciseness and usefulness of the technique. The suggested wavelets approach stands out for its simple operations, easy implementation, and accurate an

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Lin, Jing, Ming J. Zuo, and Ken R. Fyfe. "Mechanical Fault Detection Based on the Wavelet De-Noising Technique." Journal of Vibration and Acoustics 126, no. 1 (2004): 9–16. http://dx.doi.org/10.1115/1.1596552.

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For gears and roller bearings, periodic impulses indicate that there are faults in the components. However, it is difficult to detect the impulses at the early stage of fault because they are rather weak and often immersed in heavy noise. Existing wavelet threshold de-noising methods do not work well because they use orthogonal wavelets, which do not match the impulse very well and do not utilize prior information on the impulse. A new method for wavelet threshold de-noising is proposed in this paper; it not only employs the Morlet wavelet as the basic wavelet for matching the impulse, but als

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Wang, Xingjian, Bo Zhang, Fangyu Li, Jie Qi, and Bo Bai. "Seismic time-frequency decomposition by using a hybrid basis-matching pursuit technique." Interpretation 4, no. 2 (2016): T239—T248. http://dx.doi.org/10.1190/int-2015-0208.1.

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Analyzing the time-frequency features of seismic traces plays an important role in seismic stratigraphy analysis and hydrocarbon detection. The current popular time-spectrum analysis methods include short-time Fourier transform, continuous wavelet transform, S-transform, and matching pursuit (MP), among which MP is the most tolerant of the window/scalar effect. However, current MP algorithms do not consider the interfering effects of seismic events on the estimation of optimal wavelets in each decomposition iteration. The interfered reflection seismic events may result in inaccurate estimation

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Er., Balwinder Singh* Er. Surekha Rani. "PUNJABI CHARACTER RECOGNITION USING WAVELET AND CURVLET TECHNIQUES WITH SIFT ALGORITHM." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 6 (2016): 833–37. https://doi.org/10.5281/zenodo.56025.

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There are many techniques used to recognise the characters and out of these one is named as curve let technique and other is wavelet technique. The Punjabi characters has different type of patterns as compared to English characters. Curve let is a non- adaptive technique for multi scale object representation and curved singularities can be well approximated with very few coefficients and remain coherent waveforms under the action of the wave equation in a smooth medium. Standard wave let transforms for two dimensional functions have only very crude capabilities to resolve directional features.

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KHARE, ASHISH, and UMA SHANKER TIWARY. "DAUBECHIES COMPLEX WAVELET TRANSFORM BASED TECHNIQUE FOR DENOISING OF MEDICAL IMAGES." International Journal of Image and Graphics 07, no. 04 (2007): 663–87. http://dx.doi.org/10.1142/s0219467807002854.

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Wavelet based denoising is an effective way to improve the quality of images. Various methods have been proposed for denoising using real-valued wavelet transform. Complex valued wavelets exist but are rarely used. The complex wavelet transform provides phase information and it is shift invariant in nature. In medical image denoising, both removal of phase incoherency as well as maintaining the phase coherency are needed. This paper is an attempt to explore and apply the complex Daubechies wavelet transform for medical image denoising. We have proposed a method to compute a complex threshold,

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Bayjja, M., G. Alsharahi, M. Aghoutane, and N. A. Touhami. "Comparison of Wavelet Packet and Wavelet in Solving Arbitrary Array of Parallel Wires Integral Equations in Electromagnetics." Advanced Electromagnetics 9, no. 3 (2020): 8–14. http://dx.doi.org/10.7716/aem.v9i3.1487.

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In this paper, wavelets transformation (WT) and wavelet packet transformation (WPT) are used in solving, by the method of moments, a semicircular array of parallel wires electric field integral equation. First, the integral equation is solved by applying the direct method of moments via point-matching procedure, results in a linear system with a dense matrix. Therefore, wavelet transformation and wavelet packet transformation are used to sparsify the impedance matrix, using two categories of wavelets functions, Biorthogonal (bior2.2) and Orthogonal (db4) wavelets. The far-field scattering patt

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Irfan, Nagma, and A. H. Siddiqi. "An Application of Wavelet Technique in Numerical Evaluation of Hankel Transforms." International Journal of Nonlinear Sciences and Numerical Simulation 16, no. 6 (2015): 293–99. http://dx.doi.org/10.1515/ijnsns-2015-0031.

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AbstractThis paper endeavors to formulate a stable and fast algorithm for the first time that is quite accurate and fast for numerical evaluation of the Hankel transform using wavelets which are usually difficult to solve analytically so it is required to obtain the approximate solution. So we have proposed an approach depending on separating the integrand $rf(r){J_\nu}(pr)$ into two components, the slowly varying components $rf(r)$ and the rapidly oscillating component ${J_\nu}(pr)$. Then either $rf(r)$ is expanded into wavelet series using wavelets orthonormal basis which are first derived a

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Dahraoui, Nadia, M'hamed Boulakroune, S. Khelfaoui, S. Kherroubi, and Yamina Benkrima. "Effectiveness of Wavelet Denoising on Secondary Ion Mass Spectrometry Signals." East European Journal of Physics, no. 3 (September 4, 2023): 495–500. http://dx.doi.org/10.26565/2312-4334-2023-3-56.

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Wavelet theory has already achieved huge success. For Secondary Ions Mass Spectrometry (SIMS) signals, denoising the secondary signal, which is altered by the measurement, is considered that an essential step prior to applying such a signal processing technique that aims enhance the SIMS signals.The most efficient and widely used wavelet denoising method is based on wavelet coefficient thresholding. This process involves three important steps; wavelet decomposition: the input signals are decomposed into wavelet coefficients, thresholding: the wavelet coefficients are modified according to a th

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Amalia, Sitti, Mardini Hasanah, Yusreni Warmi, Novizon Novizon, and Abdul Rajab. "Disturbance Modeling on Transmission Lines Using Wavelet Transform Method: A Review." Andalas Journal of Electrical and Electronic Engineering Technology 2, no. 2 (2023): 55–61. http://dx.doi.org/10.25077/ajeeet.v2i2.31.

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This paper introduces a number of methods for identifying disturbances on transmission lines and provides algorithms for classifying various disturbance types. working with the discrete wavelets transform (DWT) and various embedded systems techniques using a simulator to carry out digital simulations of system trials using the controlled technique, the nature of disturbance in distinct sub-systems is determined. The analysis of transmission lines using the wavelet transform is the main topic of this study, along with techniques for transmission line protection. These factors include channel ca

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Vippala, Shanmukha, Gururaj Punekar, Krishnan Chemmangat, and Bhavanishanker Tangella. "A search for suitable mother wavelet in discrete wavelet transform based analysis of acoustic emission partial discharge signals." Serbian Journal of Electrical Engineering 21, no. 2 (2024): 163–85. http://dx.doi.org/10.2298/sjee2402163v.

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Signal processing helps monitor the condition of power equipment. Partial discharge (PD) signals used in condition-based maintenance give crucial information in the diagnosis of degradation of insulation. The acoustic emission technique (AET) is one of the most widely used techniques in PD signal analysis due to its inherent advantages. Analyzing acoustic emission partial discharge (AEPD) signals in the wavelet-domain provides critical insights into the location and type of the sources of PD. Selection of the most suitable mother wavelet in applying discrete wavelet transform (DWT) on AEPD sig

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Jiang, Chen, Xue Tao Weng, and Jing Jun Lou. "Gear Fault Diagnosis Based on Harmonic Wavelet Packet and BP Neural Network." Applied Mechanics and Materials 217-219 (November 2012): 2683–87. http://dx.doi.org/10.4028/www.scientific.net/amm.217-219.2683.

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The gear fault diagnosis system is proposed based on harmonic wavelet packet transform (WPT) and BP neural network techniques. The WPT is a well-known signal processing technique for fault detection and identification in mechanical system，In the preprocessing of vibration signals, WPT coefficients are used for evaluating their energy and treated as the features to distinguish the fault conditions.In the experimental work, the harmonic wavelets are used as mother wavelets to build and perform the proposed WPT technique. The experimental results showed that the proposed system achieved an averag

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OTHMANI, MOHAMED, WAJDI BELLIL, CHOKRI BEN AMAR, and ADEL M. ALIMI. "A NEW STRUCTURE AND TRAINING PROCEDURE FOR MULTI-MOTHER WAVELET NETWORKS." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 01 (2010): 149–75. http://dx.doi.org/10.1142/s0219691310003353.

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This paper deals with the features of a new wavelet network structure founded on several mother wavelets families. This new structure is similar to the classic wavelets network but it admits some differences eventually. The wavelet network basically uses the dilations and translations versions of only one mother wavelet to construct the network, but the new one uses several mother wavelets and the objective is to maximize the probability of selection of the best wavelets. Two methods are presented to assist the training procedure of this new structure. On one hand, we have an optimal selection

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Carrion, Philip M., Selma dos S. Sacramento, and Reynam da C. Pestana. "Source wavelet and its angular spectrum from plan‐wave seismograms." GEOPHYSICS 55, no. 8 (1990): 1026–35. http://dx.doi.org/10.1190/1.1442915.

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In a typical seismic experiment (land or marine), the generated source wavelet is either unknown, or known only approximately. In order to solve many geophysical problems, an accurate wavelet estimation is crucial. This paper demonstrates a fast numerical algorithm which allows not only estimating the source wavelet but also its angular spectrum (radiation pattern) from plane‐wave decomposed seismograms. Surprisingly, literature on this subject is virtually missing, although a nonuniform angular spectrum of the generated wavelet can substantially affect the recorded data. The technique present

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Arafa, Heba M., Mohamed A. Ramadan, and Nesreen Althobaiti. "A Numerical Technique Based on Bernoulli Wavelet Operational Matrices for Solving a Class of Fractional Order Differential Equations." Fractal and Fractional 7, no. 8 (2023): 604. http://dx.doi.org/10.3390/fractalfract7080604.

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In this paper, we present an efficient, new, and simple programmable method for finding approximate solutions to fractional differential equations based on Bernoulli wavelet approximations. Bernoulli Wavelet functions involve advantages such as orthogonality, simplicity, and ease of usage, in addition to the fact that fractional Bernoulli wavelets have exact operational matrices that improve the accuracy of the applied approach. A fractional differential equation was simplified to a system of algebraic equations using the fractional order integration operational matrices of Bernoulli wavelets.

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NDJOUNTCHE, TERTULIEN, and ROLF UNBEHAUEN. "IMAGE RESTORATION: THE WAVELET-BASED APPROACH." International Journal of Pattern Recognition and Artificial Intelligence 17, no. 01 (2003): 151–62. http://dx.doi.org/10.1142/s0218001403002277.

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Wavelet-based techniques are suitable for recovering a signal corrupted by noise. The time- and frequency-localization capabilities of wavelets provide better noise reduction and less signal distortion than conventional filtering methods. The noise reduction technique used in this paper is based on the hidden Markov model (HMM) structure, which can efficiently shape the statistical characteristics of practical data. As confirmed by numerical results, the HMM based approach provides a significant performance improvement over competing methods.

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Lal, Shyam, and Harish Yadav. "Approximation of functions belonging to Hölder’s class and solution of Lane-Emden differential equation using Gegenbauer wavelets." Filomat 37, no. 12 (2023): 4029–45. http://dx.doi.org/10.2298/fil2312029l.

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In this paper, a very new technique based on the Gegenbauer wavelet series is introduced to solve the Lane-Emden differential equation. The Gegenbauer wavelets are derived by dilation and translation of an orthogonal Gegenbauer polynomial. The orthonormality of Gegenbauer wavelets is verified by the orthogonality of classical Gegenbauer polynomials. The convergence analysis of Gegenbauer wavelet series is studied in H?lder?s class. H?lder?s class H?[0,1) and H?[0,1) of functions are considered, H?[0,1) class consides with classical H?lder?s class H?[0, 1) if ?(t) = t?, 0 < ? ? 1. The Gegenb

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Hinge, Gilbert, Jay Piplodiya, Ashutosh Sharma, Mohamed A. Hamouda, and Mohamed M. Mohamed. "Evaluation of Hybrid Wavelet Models for Regional Drought Forecasting." Remote Sensing 14, no. 24 (2022): 6381. http://dx.doi.org/10.3390/rs14246381.

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Drought forecasting is essential for risk management and preparedness of drought mitigation measures. The present study aims to evaluate the effectiveness of the proposed hybrid technique for regional drought forecasting. Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and two wavelet techniques, namely, Discrete Wavelet Transform (DWT) and Wavelet Packet Transform (WPT), were evaluated in drought forecasting up to a lead time of six months. Standard error metrics were used to select optimal model parameters, such as number of inputs, number of hidden neurons, level of decom

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Turiel, Antonio, Jordi Isern-Fontanet, and Emilio García-Ladona. "Wavelet Filtering to Extract Coherent Vortices from Altimetric Data." Journal of Atmospheric and Oceanic Technology 24, no. 12 (2007): 2103–19. http://dx.doi.org/10.1175/2007jtecho434.1.

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Abstract Because of the optimal features of wavelet processing, the use of wavelets for describing and analyzing signals in 2D turbulence has been generalized since a decade ago. In spite of the close analogy between 2D turbulence and geophysical fluid dynamics, few works have tried to generalize the rich framework of wavelet techniques to the study of experimental signals in oceanography. In this paper, the authors extend a prominent wavelet technique designed for the study of direct numerical simulations (DNSs) on 2D turbulence, the coherent vortex simulation, and analyze with it ocean veloc

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Zhang, Li, Charles B. Theurer, Robert X. Gao, and David O. Kazmer. "Analytic Wavelet-Based Ultrasonic Pulse Differentiation for Injection Mold Cavity Pressure Measurement." Journal of Manufacturing Science and Engineering 128, no. 1 (2005): 370–74. http://dx.doi.org/10.1115/1.2123048.

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A new signal-processing technique based on analytic wavelet transform has been developed for detecting and differentiating temporally overlapped ultrasonic pulse trains that carry spatially distributed pressure information across an injection mold cavity. Compared to conventional wavelets that have a constant relative bandwidth at all the scales, the analytic wavelets investigated in this paper feature variable relative bandwidth, making it possible to simultaneously match the frequency characteristics of the ultrasonic pulse trains transmitted from the mold-embedded pressure sensors. As a res

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Manimehalai, P., and P. Arockia Jansi Rani. "A New Robust Reversible Blind Watermarking in Wavelet-Domain for Color Images." International Journal of Image and Graphics 16, no. 02 (2016): 1650006. http://dx.doi.org/10.1142/s0219467816500066.

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Reversible watermarking methods are used for copyright protection and are able to recover the host image without distortion. Robust reversible watermarking technique should resist against intentional and unintentional image processing attacks. Robust reversible watermarking techniques should have three features namely imperceptibility, reversibility and robustness. In this paper, it is proposed to develop a new robust reversible blind watermarking for color images based on histogram construction of the wavelet coefficients constructed from the cover image. In the proposed approach, the red com

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Zhang, Rui, and Sergey Fomel. "Time-variant wavelet extraction with a local-attribute-based time-frequency decomposition for seismic inversion." Interpretation 5, no. 1 (2017): SC9—SC16. http://dx.doi.org/10.1190/int-2016-0060.1.

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Seismic impedance inversion has been widely used to estimate subsurface properties. Conventional inversion assumes that seismic data are the convolution result of seismic wavelet and reflectivity, implying that seismic data are stationary when a constant wavelet is considered. However, seismic data are nonstationary because of noise contamination and attenuation during wave propagation, which means that the frequency spectrum of the seismic signal changes from shallow to deep formations. We have developed a time-variant wavelet extraction method by using a local-attribute-based spectral decomp

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Zeelan Basha, CMAK, K. M. Sricharan, Ch Krishna Dheeraj, and R. Ramya Sri. "A Study on Wavelet Transform Using Image Analysis." International Journal of Engineering & Technology 7, no. 2.32 (2018): 94. http://dx.doi.org/10.14419/ijet.v7i2.32.13535.

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The wavelet transforms have been in use for variety of applications. It is widely being used in signal analysis and image analysis. There have been lot of wavelet transforms for compression, decomposition and reconstruction of images. Out of many transforms Haar wavelet transform is the most computationally feasible wavelet transform to implement. The wave analysis technique has an understandable impact on the removal of noise within the signal. The paper outlines the principles and performance of wavelets in image analysis. Compression performance and decomposition of images into different la

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Guillén, Daniel, Gina Idárraga-Ospina, and Camilo Cortes. "A New Adaptive Mother Wavelet for Electromagnetic Transient Analysis." Journal of Electrical Engineering 67, no. 1 (2016): 48–55. http://dx.doi.org/10.1515/jee-2016-0007.

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Abstract Wavelet Transform (WT) is a powerful technique of signal processing, its applications in power systems have been increasing to evaluate power system conditions, such as faults, switching transients, power quality issues, among others. Electromagnetic transients in power systems are due to changes in the network configuration, producing non-periodic signals, which have to be identified to avoid power outages in normal operation or transient conditions. In this paper a methodology to develop a new adaptive mother wavelet for electromagnetic transient analysis is proposed. Classification

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Sarowa, Sandeep, Naresh Kumar, and Ram Sewak Singh. "Analysis of WOFDM over LTE 1.25 MHz Band." Wireless Communications and Mobile Computing 2020 (December 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/8835879.

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Orthogonal Frequency Division Multiplexing (OFDM) is the one of the most preferred multiplexing technique for realizing high-speed wireless communication, like Long Term Evolution (LTE) and LTE-Adv. In the era of digital wireless communication, applications of wavelet theory have been favorably applied in many areas of signal processing. Orthogonality, flexible time-frequency analysis, and the ability to characterize signals accurately have attracted the attention of the telecommunication community to use wavelet as a basis function for OFDM. In this paper, discrete wavelet transform (DWT) has

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Srivastava, H. M., Firdous A. Shah, and Naied A. Nayied. "Fibonacci Wavelet Method for the Solution of the Non-Linear Hunter–Saxton Equation." Applied Sciences 12, no. 15 (2022): 7738. http://dx.doi.org/10.3390/app12157738.

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In this article, a novel and efficient collocation method based on Fibonacci wavelets is proposed for the numerical solution of the non-linear Hunter–Saxton equation. Firstly, the operational matrices of integration associated with the Fibonacci wavelets are constructed by following the strategy of Chen and Hsiao. The operational matrices merged with the collocation method are used to convert the given problem into a system of algebraic equations that can be solved by any classical method, such as Newton’s method. Moreover, the non-linearity arising in the Hunter–Saxton equation is handled by

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Surekha, Yandamuri, Akety Sai Prathyusha, K. S Ramesh, and S. Koteswara Rao. "Application of minimum phase wavelet for generation of synthetic seismic signals." International Journal of Engineering & Technology 7, no. 2.7 (2018): 212. http://dx.doi.org/10.14419/ijet.v7i2.7.10295.

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Seismic signals are analyzed by using different wavelet transforms to evaluate the magnitude of the signal. Through experimentation, it is reported that surface wave magnitude is greater than equals to three, it would affect the environment. In this paper, an attempt is made to apply minimum phase wavelet technique to analyze the seismic signals through minimum phase wavelets using CREWES data.

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Abdullah, Zainab, and Asma Abdulrahman. "Efficient object detection technique using DWT based on deep learning." International Journal of Mathematics and Computer Science 20, no. 1 (2025): 33–40. http://dx.doi.org/10.69793/ijmcs/01.2025/zainab.

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Artificial intelligence has great merit in solving many problems, such as the problem of distinguishing objects, distinguishing faces, and vehicles to determine vehicle plate numbers. With the help of image enhancement through noise reduction and image compression, the deep learning process is improved and better results are achieved. This is done by deriving new discrete wavelets from polynomials, especially Hermite polynomials (HP), to arrive at the discrete Hermite wavelet transform (DHWT) by relying on the mother wavelet and arriving at a new Hermite filter to be analyzed. Input image, den

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Safdar, Raza, Amjad Hanya, Umer Muhammad, and Khalid Aqeel. "Analysis of power system parameters for islanding detection using wavelet transform." Indonesian Journal of Electrical Engineering and Computer Science (IJEECS) 17, no. 3 (2020): 1184–93. https://doi.org/10.11591/ijeecs.v17.i3.pp1184-1193.

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This paper classifies the basic power system parameters based on sensitivity and performance capability. This is the basic step in selecting the suitable parameter for intelligent islanding detection technique. The behaviour of basic power system parameters is analyzed using wavelet transform under all possible islanding and non-islanding conditions. In wavelet transform, the mother wavelet plays a significant role in the extraction of parameter features. The db4 mother wavelet is selected after an extensive analysis on different mother wavelets. As a result, it has been found that the extract

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Maqsood, Azka, Imran Touqir, Adil Masood Siddiqui, and Maham Haider. "Wavelet Based Video Denoising using Probabilistic Models." January 2019 38, no. 1 (2019): 17–30. http://dx.doi.org/10.22581/muet1982.1901.02.

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Wavelet based image processing techniques do not strictly follow the conventional probabilistic models that are unrealistic for real world images. However, the key features of joint probability distributions of wavelet coefficients are well captured by HMT (Hidden Markov Tree) model. This paper presents the HMT model based technique consisting of Wavelet based Multiresolution analysis to enhance the results in image processing applications such as compression, classification and denoising. The proposed technique is applied to colored video sequences by implementing the algorithm on each video

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Sharif, I., and S. Khare. "Comparative Analysis of Haar and Daubechies Wavelet for Hyper Spectral Image Classification." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 937–41. http://dx.doi.org/10.5194/isprsarchives-xl-8-937-2014.

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With the number of channels in the hundreds instead of in the tens Hyper spectral imagery possesses much richer spectral information than multispectral imagery. The increased dimensionality of such Hyper spectral data provides a challenge to the current technique for analyzing data. Conventional classification methods may not be useful without dimension reduction pre-processing. So dimension reduction has become a significant part of Hyper spectral image processing. This paper presents a comparative analysis of the efficacy of Haar and Daubechies wavelets for dimensionality reduction in achiev

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Laavanya Mohan, Vijayaragahvan Veeramani,. "A COMPARATIVE STUDY OF VARIOUS WAVELET APPROACHES USED IN IMAGE DENOISING." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 1061–78. http://dx.doi.org/10.17762/itii.v9i1.238.

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The world is constantly changing, and vision helps the humans to understand the environmental changes over time. The changes can be seen by, capturing the images. Hence digital image plays a vital role in day to day life. During the process of acquisition of digital image, the qualities of digital pictures are degraded due to additive noise known as adaptive white Gaussian noise. Therefore, the major challenge of image denoising algorithm is to improve the visual appearance while preserving the other details of the image. For the last two decades, wavelet has become an elegant tool in image de

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Vimala, C., and P. Aruna Priya. "Image quality improvement using dddtdwt." International Journal of Engineering & Technology 7, no. 3.3 (2018): 416. http://dx.doi.org/10.14419/ijet.v7i2.33.14197.

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The enhancement of degraded images using different wavelet transform techniques are presented in this paper. The performance of the wavelet techniques is analysed in terms of Peak Signal to Noise Ratio values and Root Means Square error. The Double Density Dual Tree Discrete Wavelet Transform technique is mainly focused for analysis and the results are compared with discrete wavelet transform and the Double Density DWT.

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Layla A. Ahmed and Monem Mohammed. "Extend Nearly Pseudo Quasi-2-Absorbing submodules(II)." Ibn AL-Haitham Journal For Pure and Applied Sciences 36, no. 2 (2023): 420–29. http://dx.doi.org/10.30526/36.2.3060.

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Time series analysis is the statistical approach used to analyze a series of data. Time series is the most popular statistical method for forecasting, which is widely used in several statistical and economic applications. The wavelet transform is a powerful mathematical technique that converts an analyzed signal into a time-frequency representation. The wavelet transform method provides signal information in both the time domain and frequency domain. The aims of this study are to propose a wavelet function by derivation of a quotient from two different Fibonacci coefficient polynomials, as wel

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Kumar, T. K. Senthil, and E. N. Ganesh. "Proposed Technique for Accurate Detection/Segmentation of Lung Nodules using Spline Wavelet Techniques." International Journal of Biomedical Science 9, no. 1 (2013): 9–17. http://dx.doi.org/10.59566/ijbs.2013.9009.

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In this paper we are going to discuss and analyze the different methods which are developed to detect the Lung nodules which cause the lung cancer. At the end of analyzing different methods, the new methodology of detecting the lung nodules using Spline Wavelet technique has been proposed in this paper. Continuous modeling of data often required in medical imaging, Polynomial Splines are especially useful to consider image data as continuum rather than discrete array of pixels. The multi resolution property of Splines makes them prime candidates for constructing wavelet bases. Wavelet tool als

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Paul, Okuwobi Idowu, and Yong Hua Lu. "Facial Prediction and Recognition Using Wavelets Transform Algorithm and Technique." Applied Mechanics and Materials 666 (October 2014): 251–55. http://dx.doi.org/10.4028/www.scientific.net/amm.666.251.

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An efficient facial representation is a crucial step for successful and effective performance of cognitive tasks such as object recognition, fixation, facial recognition system, etc. This paper demonstrates the use of Gabor wavelets transform for efficient facial representation and recognition. Facial recognition is influenced by several factors such as shape, reflectance, pose, occlusion and illumination which make it even more difficult. Gabor wavelet transform is used for facial features vector construction due to its powerful representation of the behavior of receptive fields in human visu

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Raza, Safdar, Hanya Amjad, Muhammad Umer, and Aqeel Khalid. "Analysis of power system parameters for islanding detection using wavelet transform." Indonesian Journal of Electrical Engineering and Computer Science 17, no. 3 (2020): 1184. http://dx.doi.org/10.11591/ijeecs.v17.i3.pp1184-1193.

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<p><span>This paper classifies the basic power system parameters based on sensitivity and performance capability. This is the basic step in selecting the suitable parameter for intelligent islanding detection technique. The behaviour of basic power system parameters is analyzed using wavelet transform under all possible islanding and non-islanding conditions. In wavelet transform, the mother wavelet plays a significant role in the extraction of parameter features. The db4 mother wavelet is selected after an extensive analysis on different mother wavelets. As a result, it has been f

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Hussein, Amr, Sameh Napoleon, and Haidy Eldawy. "Performance enhancement of MPM DoA estimation technique using wavelet De-noising filter." International Journal of Engineering & Technology 5, no. 3 (2016): 66. http://dx.doi.org/10.14419/ijet.v5i3.6126.

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Direction-of-arrival (DoA) estimation is now an imperative part in many radar applications and localization techniques. There are numerous algorithms that have been studied in the previous decades for DoA, for example: MUSIC, ESPRIT, and Matrix Pencil Method (MPM), which are subspace super resolution methods. MPM is one of the most commonly used subspace based techniques. It is generally utilized for DoA estimation because of its effortlessness and high resolution contrasted with other subspace techniques. But, it suffers from performance deterioration under low Signal-to-Noise Ratio (SNR) con

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Abood, Zainab Ibrahim. "Composite Techniques Based Color Image Compression." Journal of Engineering 23, no. 3 (2017): 80–93. http://dx.doi.org/10.31026/j.eng.2017.03.06.

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Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compress

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Fu, Shengyu, B. Muralikrishnan, and J. Raja. "Engineering Surface Analysis With Different Wavelet Bases." Journal of Manufacturing Science and Engineering 125, no. 4 (2003): 844–52. http://dx.doi.org/10.1115/1.1616947.

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Traditional surface texture analysis involves filtering surface profiles into different wavelength bands commonly referred to as roughness, waviness and form. The primary motivation in filtering surface profiles is to map each band to the manufacturing process that generated the part and the intended functional performance of the component. Current trends in manufacturing are towards tighter tolerances and higher performance standards that require close monitoring of the process. Thus, there is a need for finer bandwidths for process mapping and functional correlation. Wavelets are becoming in

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M. Abduldaim, Areej, Asma Abdulelah Abdulrahman, and Fouad Shaker Tahir. "The effectiveness of discrete hermite wavelet filters technique in digital image watermarking." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 3 (2022): 1392. http://dx.doi.org/10.11591/ijeecs.v25.i3.pp1392-1399.

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<span>In this work, new discrete wavelets were derived Hermite polynomials for obtained discrete hermite wavelet transformation (DHWT), and their efficiency for use in image processing is demonstrated by proving the realization of important theorems. Moreover, the role of the new and proposed waveforms in their effective effect in placing the watermark with the color image is clarified, and a program was created using MATLAB software by creating a subprogram for constructing the new wavelet and proving its efficiency with an analytic image. The process is repeated using DHWT to analyze t

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Abduldaim, Areej M., Asma Abdulelah Abdulrahman, and Fouad Shaker Tahir. "The effectiveness of discrete hermite wavelet filters technique in digital image watermarking." Indonesian Journal of Electrical Engineering and Computer Science 25, no. 3 (2022): 1392–99. https://doi.org/10.11591/ijeecs.v25.i3.pp1392-1399.

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In this work, new discrete wavelets were derived Hermite polynomials for obtained discrete hermite wavelet transformation (DHWT), and their efficiency for use in image processing is demonstrated by proving the realization of important theorems. Moreover, the role of the new and proposed waveforms in their effective effect in placing the watermark with the color image is clarified, and a program was created using Matlab software by creating a subprogram for constructing the new wavelet and proving its efficiency with an analytic image. The process is repeated using DHWT to analyze the image. Th

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Vafaie, Sepideh, and Eysa Salajegheh. "Comparisons of wavelets and contourlets for vibration-based damage identification in the plate structures." Advances in Structural Engineering 22, no. 7 (2019): 1672–84. http://dx.doi.org/10.1177/1369433218824903.

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The objective of the present study is to compare a new approach based on contourlet transform and a traditional method based on wavelet transform to demonstrate curve damages in plate structures. The contourlet transform approach, as a novel two-dimensional development of wavelet transform, was extended to deal with inherent restrictions of wavelets. According to previous studies, wavelets have indicated poor performance to detect curve damages due to its basic elements. Therefore, this study utilized contourlet transform as a new method having an efficient performance to display this kind of

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