Results 211 to 220 of about 489,037 (244)
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Wavelets and wavelets-design issues
Proceedings of ICCS '94, 2002This paper attempts to synthesise the wavelet theories to simple design procedures so that applied researchers can readily select or design wavelets with chosen characteristics for particular applications. The paper highlights the importance of the four most desirable characteristics of wavelets for use in digital signal processing, namely ...
Thong Nguyen, Dadang Gunawan
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Wavelets and wavelet thresholding
2001Every theory starts from an idea. The wavelet idea is simple and clear. At a first confrontation, the mathematics that work out this idea might appear strange and difficult. Nevertheless, after a while, this theory leads to insight in the mechanism in wavelet based algorithms in a variety of applications.
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Discrete Wavelets and Fast Wavelet Transform
1991The wavelet analysis, introduced by J. MORLET and Y. MEYER in the middle of the eighties, is a processus of time-frequency (or time-scale) analysis which consists of decomposing a signal into a basis of functions (o jk ) called wavelets. These wavelets are in turn deduced from the analyzing wavelet o by dilatations and translations. More precisely:
Bonnet, Pierre, Rémond, Didier
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ACM Transactions on Graphics, 2005
Noise functions are an essential building block for writing procedural shaders in 3D computer graphics. The original noise function introduced by Ken Perlin is still the most popular because it is simple and fast, and many spectacular images have been made with it. Nevertheless, it is prone to problems with aliasing and detail loss.
Tony DeRose, Robert L. Cook
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Noise functions are an essential building block for writing procedural shaders in 3D computer graphics. The original noise function introduced by Ken Perlin is still the most popular because it is simple and fast, and many spectacular images have been made with it. Nevertheless, it is prone to problems with aliasing and detail loss.
Tony DeRose, Robert L. Cook
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2009
Publisher Summary This chapter highlights the use of wavelets and wavelet transforms as an alternative method of spectral analysis. It also discusses a number of common wavelets and introduces Wavelet Toolbox of the MATLAB® software. A wavelet is a function that satisfies at least the following two criteria: the integral of the function O(x) over all ...
Nicholas G. Hatsopoulos +5 more
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Publisher Summary This chapter highlights the use of wavelets and wavelet transforms as an alternative method of spectral analysis. It also discusses a number of common wavelets and introduces Wavelet Toolbox of the MATLAB® software. A wavelet is a function that satisfies at least the following two criteria: the integral of the function O(x) over all ...
Nicholas G. Hatsopoulos +5 more
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Wavelet Transforms and Wavelet Approximations
1994We summarize properties of classical wavelet transforms and Wavelet Stieltjes transforms. Wavelet approximation problems are also considered for Wavelet Stieltjes transforms. This will give rise to some characterizations of general signals.
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IEEE Transactions on Neural Networks, 1992
A wavelet network concept, which is based on wavelet transform theory, is proposed as an alternative to feedforward neural networks for approximating arbitrary nonlinear functions. The basic idea is to replace the neurons by ;wavelons', i.e., computing units obtained by cascading an affine transform and a multidimensional wavelet.
Qinghua Zhang, Albert Benveniste
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A wavelet network concept, which is based on wavelet transform theory, is proposed as an alternative to feedforward neural networks for approximating arbitrary nonlinear functions. The basic idea is to replace the neurons by ;wavelons', i.e., computing units obtained by cascading an affine transform and a multidimensional wavelet.
Qinghua Zhang, Albert Benveniste
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Wavelet and wavelet packet compression of electrocardiograms
IEEE Transactions on Biomedical Engineering, 1997Wavelets and wavelet packets have recently emerged as powerful tools for signal compression. Wavelet and wavelet packet-based compression algorithms based on embedded zerotree wavelet (EZW) coding are developed for electrocardiogram (ECG) signals, and eight different wavelets are evaluated for their ability to compress Holter ECG data.
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2012
In this chapter, we introduce the concept of wavelets and describe how to use wavelet-based decompositions in compression schemes. We begin with an introduction to wavelets and multiresolution analysis and then describe how we can implement a wavelet decomposition using filters.
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In this chapter, we introduce the concept of wavelets and describe how to use wavelet-based decompositions in compression schemes. We begin with an introduction to wavelets and multiresolution analysis and then describe how we can implement a wavelet decomposition using filters.
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Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis
Finance Research Letters, 2021John W Goodell, Stephane Goutte
exaly