Prediction occurs in many biological nervous systems e.g. in the cortex [7]. We introduce a method of adapting the recurrent layer dynamics of an echo-state network (ESN) without attempting to train the weights directly. Initially a network is generated that fulfils the echo state liquid state condition. A second network is then trained to predict the next internal state of the system. In simul...

This paper presents a robust feature extraction method effective to speech signal with high fundamental frequency and/or corrupted by additive white noise. The method represents the glottal source wave using HMM in order to model the nonstationary properties. The nodes of HMM are concatenated in a ring state to represent the periodicity of voiced sounds. The method can accurately extract glotta...

The performance of conventional digital communication schemes in the presence of additive white Gaussian noise (AWGN) has been widely studied and optimized. The efficiency of these systems, however, is severely hampered if the channel noise is impulsive. Impulsive noise is non-Gaussian in nature and is modeled well by random processes based on heavy-tailed symmetric α-stable (SαS) distributions...

Image denoising as a pre-processing stage is a used to preserve details, edges and global contrast without blurring the corrupted image. Among state-of-the-art algorithms, block shrinkage denoising is an effective and compatible method to suppress additive white Gaussian noise (AWGN). Traditional NeighShrink algorithm can remove the Gaussian noise significantly, but loses the edge information i...

The effects of additive correlated noise, which is composed of common Gaussian white noise and local Gaussian colored noise, on a square lattice network locally modelled by the Rulkov map are studied. We focus on the ability of noise to induce pattern formation in a resonant manner. It is shown that local Gaussian colored noise is able to induce pattern formation, which is more coherent at some...

We consider how the period of an oscillator is affected by white noise, with special attention given to the cases of additive noise and parameter fluctuations. Our treatment is based upon the concepts of isochrons, which extend the notion of the phase of a stable periodic orbit to the basin of attraction of the periodic orbit, and phase response curves, which can be used to understand the geome...

This paper presents a semi-analytical estimate of the response of a grandstand occupied by an active crowd and by a passive crowd. Filtered Gaussian white noise processes are used to approximate the loading terms representing an active crowd. Lumped biodynamic models with a single degree of freedom are included to reflect passive spectators occupying the structure. The response is described in ...

This paper addresses the behaviour of a classical multi-antenna GLRT test that allows to detect the presence of a known signal corrupted by a multi-path propagation channel and by an additive white Gaussian noise with unknown spatial covariance matrix. The paper is focused on the case where the number of sensors M is large, and of the same order of magnitude as the sample size N , a context whi...

Some suucient conditions to establish the rate of convergence of certain M-estimators in a Gaussian white noise model are presented. They are applied to some concrete problems, including jump point estimation and non-parametric maximum likelihood estimation, for the regression function. The results are shown by means of a maximal inequality for continuous martingales and some techniques develop...

The parabolic or forward scattering approximation has been used extensively in the study of wave propagation. This approximation is combined with a gaussian white noise approximation for waves propagating in a random medium. The validity of this approximation is proved for stratiied weakly uctuating random media in the high frequencies regime. The limiting distribution of the wave eld is charac...