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Among a variety of spectrogram methods Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) were selected to analyse transients in non-stationary tremor signals. Depending on the...
This paper compares wavelet and short time Fourier transform based techniques for single channel speechsignal noise reduction. Despite success of wavelet denoising of images, it has not yet been widel...
An Uncertainty Inequality for Wavelet Sets     Uncertainty Inequality  Wavelet Sets       font style='font-size:12px;'> 2015/9/29
The purpose of this note is to present an extension and an alternative proof to Theorem 1.3 from G. Battle (Appl. Comput. Harmonic Anal. 4 (1997) 119–146). This extension applies to wavelet Bessel set...
Stability Theorems for Fourier Frames and Wavelet Riesz Bases     Frames  Riesz basis  nonharmonic series  wavelets       font style='font-size:12px;'> 2015/9/29
In this paper we present two applications of a Stability Theorem of Hilbert frames to nonharmonic Fourier series and wavelet Riesz basis. The first result is an enhancement of the Paley-Wiener type co...
Multiresolution wavelet analysis of self-potential signals and rainfall levels is performed for extracting fluctuations in electrical signals, which might be addressed to meteorological variability. I...
Since 1996, the electric field strength of the two broadcasting stations MCO (f=216 kHz, southeast France) and CZE (f=270 kHz, Czech Republic) has been sampled every ten minutes by a receiver (AS) lo...
With ideal spatial adaptation, an oracle furnishes information about how best to adapt a spatially variable estimator, whether piecewise constant, piecewise polynomial, variable knot spline, or vari...
Pinsker(1980) gave a precise asymptotic evaluation of the minimax mean squared error of estimation of a signal in Gaussian noise when the signal is known a priori to lie in a compact ellipsoid in Hi...
EMPIRICAL BAYES SELECTION OF WAVELET THRESHOLDS     WAVELET THRESHOLDS  EMPIRICAL BAYES       font style='font-size:12px;'> 2015/8/20
This paper explores a class of empirical Bayes methods for levedependent threshold selection in wavelet shrinkage. The prior considered for each wavelet coefficient is a mixture of an atom of p...
Wavelet deconvolution in a periodic setting     Adaptive estimation  Deconvolution   Meyer wavelet       font style='font-size:12px;'> 2015/8/20
Deconvolution problems are naturally represented in the Fourier domain, whereas thresholding in wavelet bases is known to have broad adaptivity properties. We study a method which combines both fast...
Johnstone and Silverman (1997) described a level-dependent thresholding method for extracting signals from correlated noise. The thresholds were chosen to minimize a data based unbiased risk criteri...
Donoho and Johnstone (1998) studied a setting where data were obtained in the continuum white noise model and showed that scalar nonlinearities applied to wavelet coefficients gave estimators w...
Exact Risk Analysis of Wavelet Regression     Orthogonal series denoising  Squared error       font style='font-size:12px;'> 2015/8/20
Wavelets have motivated development of a host of new ideas in nonparametric regression smoothing. Here we apply the tool of exact risk analysis, to understand the small sample behavior of wavelet es...
Minimax Estimation via Wavelet Shrinkage     Minimax Decision theory  Minimax Bayes estimation       font style='font-size:12px;'> 2015/8/20
We attempt to recover an unknown function from noisy, sampled data. Using orthonormal bases of compactly supported wavelets we develop a nonlinear method which works in the wavelet domain by simple ...
Universal Near Minimaxity of Wavelet Shrinkage     Wavelet Shrinkage  Near Minimaxity       font style='font-size:12px;'> 2015/8/20
We discuss a method for curve estimation based on n noisy data; one translates the empirical wavelet coecients towards the origin by an amount p 2 log(n)  =p n. The method is nearly minimax for...

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