In this paper, a time-varying two-phase (TVTP) optimization neural network is proposed based on the two-phase neural network and the time-varying programming neural network. The proposed TVTP algorithm gives exact feasible solutions with a finite penalty parameter when the problem is a constrained time-varying optimization. It can be applied to system identification and control where it has som...

The Mobile Ad Hoc Network is an infrastructure less, multihop ad hoc network because the intermediate nodes are used to transmit data from source to destination. This paper represents the simulation based study of network protocols for varying network load and mobility. In this paper three protocols AODV, DSR and DYMO are compared by using random waypoint mobility in few nodes with varying pack...

A novel path planning approach is presented to solve optimal path in stochastic, time-varying networks under priori traffic information. Most existing studies make use of dynamic programming to find optimal path. However, those methods are proved to be unable to obtain global optimal value, moreover, how to design efficient algorithms is also another challenge. This paper employs a decision the...

The present paper discusses the stability analysis of discrete-time uncertain nonlinear systems with time-varying delay, uncertainties related to parametric uncertainty and unknown nonlinearity. The time-varying delay considered has minimum and maximum bounds. The novelty of Chebyshev Neural Network (CNN) is that it requires much less computation time as compared to multi layer neural network (...

BACKGROUND Our brains are capable of remarkably stable stimulus representations despite time-varying neural activity. For instance, during delay periods in working memory tasks, while stimuli are represented in working memory, neurons in the prefrontal cortex, thought to support the memory representation, exhibit time-varying neuronal activity. Since neuronal activity encodes the stimulus, its ...

This note develops a modelling approach for wireless networks driven by uid traÆc models. Introducing traÆc sets that follow movement of subscribers, the wireless network with time-varying rates is transformed into a stationary network at these traÆc sets, which yields that the distribution of calls over the cells of the network depends on the call length distribution only through its mean. The...

on temporal networks via adaptive rewiring Vitaly Belik,1, 2 Alexander Fengler,1 Florian Fiebig,1 Hartmut H. K. Lentz,3 and Philipp Hövel1, 4 1Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin, Germany 2Helmholtz-Zentrum für Infektionsforschung, Mascheroder Weg 1, 38124 Braunschweig, Germany 3Institute of Epidemiology, Friedrich-Loeffler-Institut...

In recent years, there has been a growing need to analyze the functional connectivity of the human brain. Previous studies have focused on extracting static or time-independent functional networks to describe the long-term behavior of brain activity. However, a static network is generally not sufficient to represent the long term communication patterns of the brain and is considered as an unrel...