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Active noise control (ANC) algorithms are generally designed to obtain the attenuation of gaussian noise signals using suitable adaptive signal processing algorithms. The rejection of non-gaussian impulsive noise signals represents a much more critical task, with respect to which standard ANC algorithms generally fail to provide a satisfactory solution, due to convergence and instability problems...
In many real-time applications the Quality of Service (QoS) is dominated by jitter. Currently jitter generators are based on Laplace distribution. Nevertheless, the observed jitter measurements depart from that distribution. As a matter of fact data resembles those of a t-Student distribution, and it is also known that Internet traffic presents heavy tailed behavior that can be modeled with alpha-stable...
Characterization of biological tissues in ultrasound images is often tackled using empirical pre-Rayleigh distributions. However, the absence of a theoretical explanation to these distributions hinders their improvement and clinical interpretation. This paper presents a novel model that extends classic statistical theories to speckle in biological tissues and explains the existing pre-Rayleigh distributions...
This paper address issues that arise in copyright protection systems of digital images, which employ blind watermark verification structures in the curvelet domain. First, we observe that statistical distribution with heavy algebraic tails, such as the alpha-stable family, are in many cases more accurate modeling tools for the curvelet coefficients than families with exponential tails such as generalized...
This paper presents a robust watermark detector in the Discrete Cosine Transform (DCT) domain. First, the watermark detection problem is formulated as a binary hypothesis testing problem according to the statistical inference. Then, the alternative current DCT coefficients are statistically modeled by symmetric alpha-stable distributions. More specifically, the scale mixture of Gaussians as an analytical...
In this paper we present the enhanced translation-invariance contourlet transform based on alpha-stable model and its application in edge detection of synthetic aperture radar (SAR) images. The translation-invariance contourlet transform is built upon the translation-invariance wavelet decomposition and nonsubsampled directional filter banks (DFB). Due to the impulsive nature of multi-revolution coefficients...
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