Stochastic Resonance and Noise-Assisted Signal Transfer : On Coupling Effects of Stochastic Resonators and Spectral Optimization of Fluctuations in Random Network Switches

Abstract: Recent research shows that noise or random fluctuations must not always be destructive in Nature by degrading system performance. On the contrary, in nonlinear systems they can synchronize systems or enhance the quality of signal transmission. The latter possibility is reported in the thesis.The phenomenon of stochastic resonance (SR) is presented and illustrated by an example of a ferromagnetically coupled spin chain, described by the Glauber's stochastic Ising spin model. It is demonstrated that an optimal strength of the next-neighbor interaction is able to improve the SR-effect. A similar mechanism has further been studied on the stochastic nonlinear dynamics of a ferromagnetic stripe domain in an inhomogeneous thin film. SR and its dependence on the domain stiffness, which is due to the exchange interaction, are presented. Experimental parameters for potential verification on Bi-doped epitaxial garnet-ferrite films are proposed. Further-on, a nonlinear model of a junction in neuronal and road structures is studied using various types of noise (stochastic processes) to generate the incoming traffic. It is shown that random fluctuations are able to enhance signal transmission, whereby the zero crossings of colored (1/fk) Gaussian noise is superior to Poissonian noise and, in certain cases, to deterministic, periodic traffic too. Optimal traffic for k ≈ 1 has been found. In case of Gaussian 1/fk noise modulated periodic input, noise-assisted traffic can be observed as well and demonstrate how random fluctuations can enhance the signal traffic efficiency in a network. The effect of an optimal k has finally been applied to a data package network switch, whereby a stochastic data scheduling algorithm is proposed and investigated numerically and analytically.