The stochastic dynamics of the Hindmarsh–Rose model of neuronal activity is studied. For the parametric zone of tonic spiking oscillations, it is shown that random disturbances transform the spiking dynamic regime into the bursting one. For a quantitative analysis of the noiseinduced bursting, we suggest a constructive approach based on the stochastic sensitivity function technique and the meth...

INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on "Biosignal Interpretation: Advanced Methods for Neural Signals and Images". BACKGROUND Dynamic Causal Modelling (DCM) is a generic formalism to study effective brain connectivity based on neuroimaging data, particularly functional Magnetic Resonance Imaging (fMRI). Recently, there have been attempts ...

The 5G network is developing rapidly. However, due to spectrum resource limitation, it expected use the ensure high utilization and efficiency, while keeping part of 4G in same band for existing users. Dynamic spectrum-sharing (DSS) technology enables 4G/5G wireless networks coexist scarce resources dynamically allocates band. DSS has been successfully commercialized some countries such as Germ...

This paper aims at proposing a quadratic assignment-based mathematical model to deal with the stochastic dynamic facility layout problem. In this problem, product demands are assumed to be dependent normally distributed random variables with known probability density function and covariance that change from period to period at random. To solve the proposed model, a novel hybrid intelligent algo...

Several peculiarities of stochastic dynamic programming problems where random vectors are observed before the decision is made at each stage are discussed in the first part of this paper. Surrogate problems are given for such problems with distance properties (for instance, transportation problems) in the second part.

In the deterministic context a series of well established results allow to reformulate delay differential equations (DDEs) as evolution equations in infinite dimensional spaces. Several models in the theoretical economic literature have been studied using this reformulation. On the other hand, in the stochastic case only few results of this kind are available and only for specific problems. The...

in this paper, intelligent algorithm of ALATO based on Learning Automata using Adaptive Stochastic Petri Net presented to optimize the time in Economical Grid. Adaptive Stochastic Petri nets based on learning automata predicts the following optimized state through getting information from former system states and dynamic environmental reactions, makes the system current states appeared based on...