Most of the research performed in the area of turbo codes has considered only Additive White Gaussian Noise (AWGN) channels. While some work has extended the coverage of channel noise to fading channels, thus far little research has been performed with heavy-tailed noise distributions. This paper analyzes the performance of the turbo decoder for a class of heavy-tailed noise distributions consi...

A method for synthesizing a matched filter conditions of simultaneous action white noise and non-Gaussian is proposed. The based on the representation as linear system that implements an integral transformation with real kernel. Noise, signal are considered to be frequency limited. signal-to-noise ratio at reference point in time determined. expansion correlation function interference into seri...

We consider the Kuramoto model of globally coupled phase oscillators with time-delayed interactions, that is subject to Ornstein–Uhlenbeck (Gaussian) colored or non-Gaussian colored noise. We investigate numerically the interplay between the influences of the finite correlation time of noise τ and the time delay τd on the onset of the synchronization process. The cases for identical and noniden...

in this work the performance of a wavelength division multiple access (wdma) system with direct detection receiver is investigated. for this purpose, the probability of error in a wdma network with ook modulation considering crosstalk, isi, photo detector noise and thermal noise is calculated and the effect of each on system performance is investigated. the system performance in presence of pin...

Although typical model-based noise suppression including the vector Taylor series-based approach employs a single Gaussian distribution for the noise model, it is insufficient for nonstationary noises which have a complex structured distribution. As a solution to this problem, we have already proposed a method for estimating a Gaussian mixture model (GMM)-based noise model by using a minimum me...

The problem of detecting a signal known except for amplitude in incompletely characterized colored non-Gaussian noise is addressed. The problem is formulated as a testing of composite hypotheses using parametric models for the statistical behavior of the noise. A generalized likelihood ratio test is employed. It is shown that for a symmetric noise probability density function the detection perf...

Here we study a noise induced transition when the system is driven by a noise source taken as colored and non-Gaussian. We show –using both, a theoretical approximation and numerical simulations– that there is a shift of the transition as the noise departs from the Gaussian behavior. Also, we confirm the reentrance effect found for colored Gaussian noise and show the behavior of the transition ...

Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equatio...

In recent years, correntropy and its applications in machine learning have been drawing continuous attention owing to its merits in dealing with non-Gaussian noise and outliers. However, theoretical understanding of correntropy, especially in the statistical learning context, is still limited. In this study, within the statistical learning framework, we investigate correntropy based regression ...

We consider Gaussian, Poissonian, fractional Gaussian and fractional Poissonian white noise spaces, all represented through the corresponding orthogonal basis of the Hilbert space of random variables with finite second moments, given by the Hermite and the Charlier polynomials. There exist unitary mappings between the Gaussian and Poissonian white noise spaces. We investigate the relationship o...