Abstract Likelihood analysis is typically limited to normally distributed noise due the difficulty of determining probability density function complex, high-dimensional, non-Gaussian, and anisotropic noise. This a major limitation for precision measurements in many domains science, including astrophysics, example, cosmic microwave background, gravitational waves, lensing, exoplanets. work prese...

Digital image is often degraded by many kinds of noise during the process of acquisition and transmission. To make subsequent processing more convenient, it is necessary to decrease the effect of noise. There are many kinds of noises in image, which mainly include salt and pepper noise and Gaussian noise. This paper focuses on median filters to remove the salt and pepper noise. After summarizin...

This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...

Objective(s): In order to evaluate the effect of post-reconstruction Gaussian filtering on image quality and myocardial blood flow (MBF) measurement by dynamic N-13 ammonia positron emission tomography (PET), we compared various reconstruction and filtering methods with image characteristics. Methods: Dynamic PET images of three patients with coronary artery disease (male-female ratio of 2:1; a...

In this paper an estimator for speech enhancement based on Laplacian Mixture Model has been proposed. The proposed method, estimates the complex DFT coefficients of clean speech from noisy speech using the MMSE  estimator, when the clean speech DFT coefficients are supposed mixture of Laplacians and the DFT coefficients of  noise are assumed zero-mean Gaussian distribution. Furthermore, the MMS...

in this paper, we present the numerical solution of ordinary dierential equations (or sdes), from each order especially second-order with time-varying and gaussian random coecients. we indicate a complete analysis for second-order equations in special case of scalar linear second-order equations (damped harmonic oscillators with additive or multi- plicative noises). making stochastic dierent...