in the present article, we focus on the numerical approximation of stochastic partial differential equations of itˆo type with space-time white noise process, in particular, parabolic equations. for each case of additive andmultiplicative noise, the numerical solution of stochastic diffusion equations is approximated using two stochastic finite difference schemes and the stability and consisten...

The recently proposed additive noise model has advantages over previous directed structure learning approaches since it (i) does not assume linearity or Gaussianity and (ii) can discover a unique DAG rather than its Markov equivalence class. However, for certain distributions, e.g. linear Gaussians, the additive noise model is invertible and thus not useful for structure learning, and it was or...

This paper introduces our actual work in front-end techniques to obtain robust speech recognition devices in mismatch conditions (additive noise mismatch and channel mismatch). Two algorithms have been combined to compensate the distortions due to different channel characteristics and additive noise: 1) A Cepstral Mean Normalization and Variance Scaling technique (MNVS) and 2) An Adaptive Gauss...

Frequency-resolved optical gating (FROG), a technique for measuring ultrashort laser pulses, involves producing a spectrogram of the pulse and then retrieving the pulse intensity and phase with an iterative algorithm. We study how several types of noise—multiplicative, additive, and quantization—affect pulse retrieval. We define a convergence criterion and find that the algorithm converges to a...

The maximum entropy noise under a lag autocorrelation constraint is known by Burg’s theorem to be the th order Gauss–Markov process satisfying these constraints. The question is, what is the worst additive noise for a communication channel given these constraints? Is it the maximum entropy noise? The problem becomes one of extremizing the mutual information over all noise processes with covaria...

The standard tool to estimate the phase of a sequence of phase-shifted interferograms is the Phase Shifting Algorithm (PSA). The performance of PSAs to a sequence of interferograms corrupted by non-white additive noise has not been reported before. In this paper we use the Frequency Transfer Function (FTF) of a PSA to generalize previous white additive noise analysis to non-white additive noisy...

Asymptotic properties of two time-scale stochastic approximation algorithms with constant step sizes are analyzed in this paper. The analysis is carried out for the algorithms with additive noise, as well as for the algorithms with non-additive noise. The algorithms with additive noise are considered for the case where the noise is state-dependent and admits the decomposition as a sum of a mart...

Digital images are mostly corrupted by mixed noise from several sources. It is a challenging problem to remove mixed noise in color images. Generally, some image denoising filters can reduce either additive or impulse noise, but it fails to remove both impulsive noise and additive noise. This paper presents modified bilateral filtering method, which can simultaneously remove both impulsive and ...

In this paper a novel nonuniformity correction method that compensates for the fixed-pattern noise (FPN) in infrared focal-plane array (IRFPA) sensors is developed. The proposed NUC method compensates for the additive component of the FPN statistically processing the read-out signal using a noise-cancellation system. The main assumption of the method is that a source of noise correlated to the ...