搜索结果: 1-15 共查到“数学 wavelet”相关记录36条 . 查询时间(0.057 秒)
Comparison of Wavelet and FFT Based Single Channel Speech Signal Noise Reduction Techniques
DWT DWPT wavelet wavelet packet FFT noise control speech enhancement noise cancellation filter
2015/9/29
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...
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
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...
Ideal Spatial Adaptation by Wavelet Shrinkage
Minimax estimation sub ject to doing well at a point Orthogonal Wavelet Bases of Compact Support
2015/8/20
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...
Minimax Bayes, asymptotic minimax and sparse wavelet priors
Minimax Decision theory Minimax Bayes estimation
2015/8/20
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...
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
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...
WAVELET SHRINKAGE FOR CORRELATED DATA AND INVERSE PROBLEMS: ADAPTIVITY RESULTS
Adaptation correlated data fractional brownian motion
2015/8/20
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...
ASYMPTOTIC MINIMAXITY OF WAVELET ESTIMATORS WITH SAMPLED DATA
Besov spaces bounded operators between Besov spaces
2015/8/20
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...
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...
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 ...
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...
Density estimation is a commonly used test case for non-parametric estimation
methods. We explore the asymptotic properties of estimators based on thresholding of
empirical wavelet coecients. Minim...
Considerable e ort has been directed recently to develop asymptotically minimax methods in problems of recovering in nite-dimensional ob jects (curves, densities, spectral densities, images) from nois...
Power Tensor Theory and Continuous Wavelet Transform
Wavelets Tensor Electrical Power Power Electronic Power Quality
2013/1/30
A model for the definition of electrical Power is presented, which retrieves the concepts of homomorphism from the geometrical tensor approximation at the wavelet approach. Their definition here is ne...