An ensemble of stochastic non-leaky integrate-and-fire neurons with global, delayed and excitatory coupling and a small refractory period is analyzed. Simulations with adiabatic ...
Stochastic Flow Models (SFMs) are stochastic ystems that abstract the dynamics of complex discrete event systems involving the control of sharable resources. SFMs have been used to...
From the phosphorylation state of a molecule to the volume of a cell, parameters are ubiquitous in systems biology. At the same time, most models involve static or dynamic compart...
Background: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuation...
Howard Salis, Vassilios Sotiropoulos, Yiannis N. K...
A control of real processes requires different approach to neural network learning. The presented modification of backpropagation learning algorithm changes a meaning of learning...