Virtually all real-world networks are dynamical entities. In social networks, the propensity of nodes to engage in social interactions (activity) and their chances to be selected by active nodes (attractiveness) are heterogeneously distributed. Here, we present a time-varying network model where each node and the dynamical formation of ties are characterized by these two features. We study how ...

The use of particle filters for the prediction of time series arising from chaotic dynamical systems is explored. The specific dynamical systems considered are variations of the logistical map with an unknown parameter. This parameter is in the chaotic regime for these dynamical systems. The systems considered have both observation and process noise. The prediction algorithms studied are variat...

We clarify the radion superfield dependence of 5D N = 1 superspace action. The radion is treated as a dynamical field and appears in the action with the correct mode function. Our derivation is systematic and based on the superconformal formulation of 5D supergravity. We can read off the couplings of the dynamical radion superfield to the matter superfields from our result. The correct radion m...

In this paper the basic methodology of the coupled response-degradation modelling of stochastic dynamical systems is presented along with the effective analysis of selected problems. First, the general formulation of the problems of stochastic dynamics coupled with the evolution of deterioration process is given. Then some specific degrading oscillatory systems under random excitation are analy...

Using Dirac’s approach to constrained dynamics, the Hamiltonian formulation of regular higher order Lagrangians is developed. The conventional description of such systems due to Ostrogradsky is recovered. However, unlike the latter, the present analysis yields in a transparent manner the local structure of the associated phase space and its local sympletic geometry, and is of direct application...

A central problem of dynamical systems theory is to identify a reduced description of the dynamical process one can deal easier. In this paper we present a systematic method of identifying those closed sub-systems of a given discrete time dynamical system in the frame of operator theory. It is shown that this problem is closely related to finding invariant sigma algebras of the dynamics. Index ...

While spiral wave breakup has been implicated in the emergence of atrial fibrillation, its role in maintaining this complex type of cardiac arrhythmia is less clear. We used the Karma model of cardiac excitation to investigate the dynamical mechanisms that sustain atrial fibrillation once it has been established. The results of our numerical study show that spatiotemporally chaotic dynamics in ...

Many published papers analyzed the forming mechanisms and evolution laws of OO software systems from software reuse, software pattern, etc. There, however, have been fewer models so far merely built on the software components such as methods, classes, etc. and their interactions. In this paper, a novel Software Evolution Model based on Software Networks (called SEM-SN) is proposed. It uses soft...

ÐStandard, exact techniques based on likelihood maximization are available for learning Auto-Regressive Process models of dynamical processes. The uncertainty of observations obtained from real sensors means that dynamics can be observed only approximately. Learning can still be achieved via aEM-KoÐExpectation-Maximization (EM) based on Kalman Filtering. This cannot handle more complex dynamics...

In this paper a grey-box model of a nonlinear dynamical system is constructed. This involves using a Gaussian process to emulate model error the error that arises as a result of flaws in one’s physical-law based model of the system. The work shows how such an approach can be extended towards dynamical systems. Specifically, it is applied to experimental data, obtained from a dynamical system wh...