In a recent paper, de Forcrand has pointed out that matrix inversions using Gaussian noise need not be iterated to full convergence, but instead may be solved approximately and treated as a heatbath. Gaussian noise however is not optimal for minimizing variance. It shown here how his algorithm may be generalized to a mixture of Gaussian and Z(N) noise, resulting in a smaller effective variance ...

In radar tracking application, the observation noise is highly non-Gaussian, which is also referred as glint noise. The performance of extended Kalman filter degrades severely in the presence of glint noise. In this paper, an improved particle filter, Markov chain Monte Carlo particle filter (MCMC-PF), is introduced to cope with radar target tracking in glint noise environment. The Monte Carlo ...

Gaussian/non-Gaussian impulsive noises in underwater acoustic (UWA) channel seriously impact the quality of communication. The common denoising algorithms are based on Gaussian noise model and difficult to apply coexistence noises. Therefore, a new UWA is described this paper by combining symmetric ?-stable (S?S) distribution normal distribution. Furthermore, novel signal algorithm called AWMF+...

A bistable toggle switch is a paradigmatic model in the field of biology. The dynamics of the system induced by Gaussian noise has been intensively investigated, but Gaussian noise cannot incorporate large bursts typically occurring in real experiments. This paper aims to examine effects of variations from one protein imposed by a non-Gaussian Lévy noise, which is able to describe even large ju...

In this paper, a new combination of Minimum Description Length (MDL) or Eigenvalue Gradient Method (EGM), Joint Approximate Diagonalization of Eigenmatrices (JADE) and Modified Forward-Backward Linear Prediction (MFBLP) algorithms is proposed which determines the number of non-coherent source groups and estimates the Direction Of Arrivals (DOAs) of coherent signals in each group. First, the MDL...