The conditional Gauss-Hermite filter(CGHF) utilizes a decomposition of the filter density p(y1,y2) into the product of the conditional density p(y1Iy2) with the P(y2) where the state vector y is partitioned into (y1,y2). In contrast the usual Gauss-Hermite filter (GHF) it is assumed that the...

The probability density function of the response of a nonlinear system under external α-stable Lévy white noise is ruled by the so called Fractional Fokker–Planck equation. In such equation the diffusive term is the Riesz fractional derivative of the probability density function of the...

In this paper it is shown that a nonlinear system with an isolated equilibrium can be identified using two kinds of Dynamic Neural Networks, the Hopfield type (DNN-H) and the Multilayer type (DNN-M). The identified models are in continuous time. The equilibrium point is assumed to be the origin,...

Two types of models can be used to describe nonlinear agricultural systems: mechanistic and empirical. For the first type of models, mathematical methods for simulating, a set of differential equations which characterise the underpinning process relationships are outlined. For the second type of...

This paper deals with the effects of stochastic resonance in some sorts of nonlinear dynamic systems on multi-frequency signal processing in the presence of white or colored noise. By means of tuning system parameters and changing the nonlinear systems, the ability of the systems driven by noise...

We undertake the study of human EEG-signals by recourse to a wavelet based multiresolution analysis as adapted to an Information-Measure-Scenario. Different information measures are employed. It is shown that non-extensive ones seem to be of particular usefulness. Their use opens up perspectives...

The Faà di Bruno formula enables us to compute the derivatives of a function of several variables. We show here, in spite of the noncommutativity of causal computations, that the Faà di Bruno grammar makes it possible to compute the derivatives of any causal functional. Using this property and...

In this paper we describe the design of a control algorithm for MISO systems, which can be modelled as hybrid fuzzy models. Hybrid fuzzy models present a convenient approach to modelling nonlinear hybrid systems.

This paper deals with the automatic detection of slight parameter changes from the analysis of signals generated by nonlinear biological systems. The interest is focused here on investigating particular aspects of the relation between signal analysis and systems dynamics, involving the automatic...