In order to separate super-Gaussian and sub-Gaussian signals,this paper uses high-and low-frequency coefficients of wavelet transform as smooth factors,then builds a signal-to-noise ratio objective function,which uses the denominator as prediction error and can be optimized to resolve separable matri...
Ideal denoising for signals in sub-Gaussian noise[J].Applied and Computational Harmonic Analysis,2008,(01):1-13.S.E. Ferrando, R. Pyke, Ideal denoising for signals in sub-Gaussian noise, Appl. Comput. Harmon. Anal. 24(1) (2008) 1-13....
The present paper concentrates in extending and improving this result, the main contribution is to incorporate a wider class of noise vectors. The class of strict sub-Gaussian random vectors allow us to obtain large deviation inequalities in a uniform way over all basis in a given library. The...
The existing algorithms for adaptive filtering do not provide a better performance than the least mean square (LMS) method for the super- and sub-Gaussian noise simultaneously. For example, the maximum correntropy criterion performs better (worse) than the LMS method for super-Gaussian (sub-...
In the presence of heavy-tailed noise Interference, this suboptimum processor approach loses on the order of 1 dB In signal detectability relative to the optimum processor. Lack of the detailed signal structure is not a detriment to this processor; furthermore, the information required to realize...
The use of the R sub 0 criterion for modulation system design is investigated for channels with non-white Gaussian noise. A signal space representation of the waveform channel is developed, and the cut-off rate R sub 0 for vector channel... IC Wong,BL Evans\T 被引量: 0发表: 2017年 加...
In order to separate super-Gaussian and sub-Gaussian signals,this paper uses high-and low-frequency coefficients of wavelet transform as smooth factors,then builds a signal-to-noise ratio objective function,which uses the denominator as prediction error and can be optimized to resolve separable matri...
strict sub-gaussian noiseDonoho and Johnstone introduced an algorithm and supporting inequality that allows the selection of an orthonormal basis for optimal denoising. The present paper concentrates in extending and improving this result, the main contribution is to incorporate a wider class of noise ...
We then show theoretically and demonstrate numerically, on synthetically generated signals, that whereas the case of constant a is consistent with a collection of samples from truncated sub-Gaussian fractional Levy noise, a random field (or process) subordinated to truncated fractional Gaussian noise, ...
However, the characteristics of the propagation channel at such high frequencies differ from what is observed in the conventional low-frequency spectrum with for instance, the apparition of stronger phase noise (PN) induced by the Radio Frequency (RF) transceivers and more especially by the ...