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The wavelet analysis technique is a powerful tool and is widely used in broad disciplines of engineering, technology, and sciences. In this work, we present a novel scheme of constructing continuous wavelet functions, in which the wavelet…

Instrumentation and Methods for Astrophysics · Physics 2021-08-06 Yun Wang , Ping He

Several differentiating algorithms of the noisy signals are considered. The proposed wavelet based technique is compared with others based on the Fourier transform and the finite differences. The accuracy of the calculations for different…

Mathematical Physics · Physics 2007-05-23 I. Patrickeyev , R. Stepanov , P. Frick

Both of Wavelet and Fast Fourier Transform are strong signal processing tools in the field of Data Analysis. In this paper fast fourier transform (FFT) and Wavelet Transform are employed to observe some important features of Solar image…

Computer Vision and Pattern Recognition · Computer Science 2013-12-11 Sabyasachi Mukhopadhyay , Debadatta Dash , Swapnil Barmase , Prasanta K Panigrahi

In this paper high resolution wave probe records are examined using wavelet techniques with a view to determining the sources and relative contributions of capillary wave energy along representative wind wave forms. Wavelets enable…

Fluid Dynamics · Physics 2017-06-27 F. C. G. A. Nicolleau , J. C. Vassilicos

The influence of higher-order wavelet properties on the analytic wavelet transform behavior is investigated, and wavelet functions offering advantageous performance are identified. This is accomplished through detailed investigation of the…

Methodology · Statistics 2011-10-18 J. M. Lilly , S. C. Olhede

We study the use of the quantum wavelet transform to extract efficiently information about the multifractal exponents for multifractal quantum states. We show that, combined with quantum simulation algorithms, it enables to build quantum…

Quantum Physics · Physics 2009-09-24 I. Garcia-Mata , O. Giraud , B. Georgeot

The properties of the Gabor and Morlet transforms are examined with respect to the Fourier analysis of discretely sampled data. Forward and inverse transform pairs based on a fixed window with uniform sampling of the frequency axis can…

Data Analysis, Statistics and Probability · Physics 2013-07-23 Robert W. Johnson

This note is a very basic introduction to wavelets. It starts with an orthogonal basis of piecewise constant functions, constructed by dilation and translation. The ``wavelet transform'' maps each $f(x)$ to its coefficients with respect to…

Numerical Analysis · Mathematics 2025-10-20 Gilbert Strang

It is shown that any convolution operator in the time domain can be represented exactly as a multiplication operator in the time-scale (wavelet) domain. The Mellin transform gives a one-to-one correspondence between frequency filters…

Mathematical Physics · Physics 2007-05-23 Gerald Kaiser

We propose a new method for (global) Hurst exponent determination based on wavelets. Using this method, we analyze synthetic data with predefined Hurst exponents, fracture surfaces and data from economy. The results are compared with those…

Materials Science · Physics 2010-05-04 Ingve Simonsen , Alex Hansen , Olav Magnar Nes

Wavelet transforms are widely used in various fields of science and engineering as a mathematical tool with features that reveal information ignored by the Fourier transform. Unlike the Fourier transform, which is unique, a wavelet…

Quantum Physics · Physics 2024-04-23 Mohsen Bagherimehrab , Alan Aspuru-Guzik

Some general remarks about integral transform approaches to response functions are made. Their advantage for calculating cross sections at energies in the continuum is stressed. In particular we discuss the class of kernels that allow…

Nuclear Theory · Physics 2017-03-08 Giuseppina Orlandini , Francesco Turro

This paper develops a threshold model with a time-varying threshold, represented using a wavelet series expansion. The model adequately captures irregular and abrupt variations, as well as smooth changes in the threshold parameter, allowing…

Methodology · Statistics 2026-05-19 Rhea Davis , N. Balakrishna

Accurate predictions of inclusive scattering cross sections in the linear response regime require efficient and controllable methods to calculate the spectral density in a strongly-correlated many-body system. In this work we reformulate…

Quantum Physics · Physics 2023-03-29 Jeremy Hartse , Alessandro Roggero

In this paper we outline several points of view on the interplay between discrete and continuous wavelet transforms; stressing both pure and applied aspects of both. We outline some new links between the two transform technologies based on…

Computational Engineering, Finance, and Science · Computer Science 2011-11-09 Palle E. T. Jorgensen , Myung-Sin Song

A wavelet transform spectrum analyzer operating in real time within the frequency range 3X10^(-5) - 1.3X10^5 Hz has been implemented on a low-cost Digital Signal Processing board operating at 150MHz. The wavelet decomposition of the signal…

Statistical Mechanics · Physics 2009-11-07 Doriano Brogioli , Alberto Vailati

Wavelet analysis is proposed as a new tool for studying the large-scale structure formation of the universe. To reveal its usefulness, the wavelet decomposition of one-dimensional cosmological density fluctuations is performed. In contrast…

Astrophysics · Physics 2009-10-28 Yoshi Fujiwara , Jiro Soda

This review paper is intended to give a useful guide for those who want to apply discrete wavelets in their practice. The notion of wavelets and their use in practical computing and various applications are briefly described, but rigorous…

High Energy Physics - Phenomenology · Physics 2025-10-20 I. M. Dremin , O. V. Ivanov , V. A. Nechitailo

It is demonstrated that the wavelets can be used to considerably speed up simulations of the wave packet propagation in multiscale systems. Extremely high efficiency is obtained in the representation of both bound and continuum states. The…

Computational Physics · Physics 2009-11-07 Andrei G. Borisov , Sergei V. Shabanov

Wavelet Transforms are a widely used technique for decomposing a signal into coefficient vectors that correspond to distinct frequency/scale bands while retaining time localization. This property enables an adaptive analysis of signals at…

Applications · Statistics 2025-11-05 Jack Kissell , Vijini Lakmini , Brani Vidakovic