We investigate the regularizing effect of certain additive continuous perturbations on SDEs with multiplicative fractional Brownian motion (fBm). Traditionally, a Lipschitz requirement drift and diffusion coefficients is imposed to ensure existence uniqueness SDE. show that suitable restore existence, regularity flow for resulting equation, even when both are distributional, thus extending prog...

This paper presents a novel feature extraction approach for speaker identification when the speech is corrupted by additive noise. The environmental mismatch between training and testing data degrades the performance of speaker identification system. The performance degradation is primarily due to presence of background noise when try to match a given speaker to the set of known speakers in a d...

It is well known that the performance of an automatic speaker recognition system degrades in the presence of noise. The degradation of voice due to the presence of additive background noise and convolutive noise causes severe difficulties in various communication environments. This paper addresses the problem of reduction of additive as well as convolutive noise in speech. This paper explores a...

The speech enhancement problem comprises of various problems characterized by the type of noise source, the nature of interaction between speech and noise, the number of sensor signals (microphone outputs) available for enhancement and the nature of the speech application. Noise reduction remains a demanding problem due to wide variety of background noise types (car noise, babble noise, cockpit...

In image processing, image is corrupted by different type of noises. But generally medical image is corrupted by speckle noise. So image de-noising has become a very essential exercise all through the diagnose. Noises are of two type additive and multiplicative noise. Speckle noise is multiplicative noise, so it’s difficult to remove the multiplicative noise as compared to additive noise. The t...

The optimal detection of a signal of known form hidden in additive white noise is examined in the framework of stochastic resonance and noise-aided information processing. Conditions are exhibited where the performance in the optimal detection increases when the level of the additive (non-Gaussian bimodal) noise is raised. On the additive signal–noise mixture, when a threshold quantization is p...