Beta through the prism of wavelets by Aasif Shah, Arif Tali, Qaiser Farooq

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On the Exact Evaluation of Integrals of Wavelets by Enza Pellegrino, Chiara Sorgentone, Francesca Pitolli

Subjects: “…wavelet…”
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Wavelets for Electrocardiogram: Overview and Taxonomy by Wei Li

Subjects: “…Wavelets for electrocardiogram…”
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Wavelets and Lattice Field Theory. by Neuberger Herbert

“…When continuous fields are expanded in a wavelet basis, a D-dimensional continuum action becomes a (D+1)-dimensional lattice action on the naively discretized Poincare-patch coordinates of an Euclidean AdS(D+1). …”
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Wavelet-Based Monitoring for Biosurveillance by Galit Shmueli

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Noiseless Codelength in Wavelet Denoising by Azadeh Fakhrzadeh, Soosan Beheshti, Sridhar Krishnan

“…Simulation results are presented for orthonormal wavelet transforms. While the method is comparable with the existing thresholding methods and in some cases outperforms them, the main advantage of the new approach is that it provides not only the optimum threshold but also an estimate of the associated mean-square error (MSE) for that threshold simultaneously.…”
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On wavelet type Bernstein operators by H. Karsli

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Wavelets in Recognition of Bird Sounds by Selin Arja, Turunen Jari, Tanttu Juha T

“…The recognition algorithm consists of feature extraction using wavelet decomposition and recognition using either supervised or unsupervised classifier. …”
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Birdsong Denoising Using Wavelets. by Nirosha Priyadarshani, Stephen Marsland, Isabel Castro, Amal Punchihewa

“…We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings.…”
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Wavelet filtering of chaotic data by M. Grzesiak

“…Normally it is necessary to assume certain properties of the noise and dynamics, which one wants to extract, from time series. The wavelet based method of denoising of time series originating from low-dimensional dynamical systems and polluted by the Gaussian white noise is considered. …”
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Noiseless Codelength in Wavelet Denoising by Beheshti Soosan, Fakhrzadeh Azadeh, Krishnan Sridhar

“…Simulation results are presented for orthonormal wavelet transforms. While the method is comparable with the existing thresholding methods and in some cases outperforms them, the main advantage of the new approach is that it provides not only the optimum threshold but also an estimate of the associated mean-square error (MSE) for that threshold simultaneously.…”
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Application of wavelets to speech coding by Ooi, James M., 1970-

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Wavelets : a conceptual overview

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Parsimony and wavelet methods for denoising

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Wavelet Domain Geophysical Inversion by Kane, Jonathan, Herrmann, Felix, Toksoz, M. Nafi

“…We present a non-linear method for solving linear inverse problems by thresholding coefficients in the wavelet domain1. Our method is based on the wavelet-vaguelette decomposition of Donoho (1992). …”
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Wavelet-based image compression by Chen, Shuran.

“…This thesis on the project work consists of three major parts: wavelet theory overview, comparative study, and development of wavelet-based image compression algorithms.…”
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Wavelet filters in image compression by Janardhana Bhat

“…In this study, we mainly study the concepts of wavelet transformation starting from Fourier Transformation. …”
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Wavelets image data compression by Khalifa, Othman Omran, Dlay, Satnam Singh

“…In this paper we combiire a wavelet transform with vector quantization, usin!! …”
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Sequential Bayesian wavelet denoising by Coates, M, Doucet, A

“…We propose a wavelet model that incorporates coefficient correlation and is expressed in state-space form, allowing the development and application of sequential estimation algorithms for wavelet denoising. …”

Wavelet-based voice morphing by Orphanidou, C, Moroz, I, Roberts, S

“…The voice morphing algorithm performs the morphing at different subbands by using the theory of wavelets and models the spectral conversion using the theory of Radial Basis Function Neural Networks. …”