It is well known that Inertial Navigation Systems (INS) can provide high accuracy information on the position, velocity, and attitude over a short time period. However, their accuracy degrades rapidly with time. The requirements for accurate estimation of navigation information necessitate the modeling of the sensors' noise components. Several methods have been devised for stochastic modeling o...

In the cerebral cortex of awake animals, neurons are subject to a tremendous fluctuating activity mostly of synaptic origin and termed “synaptic noise”. Synaptic noise is the dominant source of membrane potential fluctuations in neurons and can have a strong influence on their integrative properties. We review here the experimental measurements of synaptic noise, and its modeling by conductance...

Kernel methods are very popular for static modeling, i.e. classification or nonlinear regression. Only few attempts have been made at extending the concepts to dynamic modeling, i.e. models where some or all variables of the model are the predictions provided by the model at previous sampling times. The feedback thus introduced results in an increased complexity; it is well known, however, that...

Parametric modeling strategies are explored in conjunction with Linear Discriminant Analysis (LDA) to facilitate an Electroencephalogram (EEG) based direct-brain interface. A left/right self-paced typing exercise is analysed by employing an AutoRegressive (AR) model for feature extraction and an AutoRegressive with Exogenous input (ARX) model for combined filtering and feature extraction. Model...

We study the related problems of denoising images corrupted by impulsive noise and blind inpainting (i.e., inpainting when the deteriorated region is unknown). Our basic approach is to model the set of patches of pixels in an image as a union of low dimensional subspaces, corrupted by sparse but perhaps large magnitude noise. For this purpose, we develop a robust and iterative method for single...

We propose a exible analysis/synthesis model for transient signals that eeectively extends the Spectral Modeling Synthesis (SMS) parameterization of signals from sinusoids+noise to sinu-soids+transients+noise. The explicit handling of transients provides a more realistic and robust signal model. The model presented is a parametric model for transients that allows for a wide range of signal tran...

We discuss tools for calculating divergence-free fields for artistic particle simulations. We introduce a simple, fast divergence-free noise function which can be used for turbulence. We also describe how the interpolation technique used by the noise function can be used for calculating artist-controlled divergence-free fields. The artist can create realistic unbounded flow fields without the c...

This paper introduces modeling and simulation of the noise properties of the blue-violet InGaN laser diodes. The noise is described in terms of the spectral properties of the relative intensity noise (RIN). We examine the validity of the present noise modeling by comparing the simulated results with the experimental measurements available in literature. We also compare the obtained noise result...

Shot-noise processes generalize compound Poisson processes in the following way: a jump (the shot) is followed by a decline (noise). This constitutes a useful model for insurance claims in many circumstances; claims due to natural disasters or self-exciting processes exhibit similar features. We give a general account of shot-noise processes with time-inhomogeneous drivers inspired by recent re...