Activity-driven modeling has been recently proposed as an alternative growth mechanism for time varying networks, displaying power-law degree distribution in time-aggregated representation. This approach assumes memoryless agents developing random connections, thus leading to random networks that fail to reproduce two-nodes degree correlations and the high clustering coefficient widely observed...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

The Gaussian arbitrarily varying channel with input constraint r and state constraint 2 admits input sequences x = ( x l , , x , ~ ) of real numbers with Cxf 5 nT and state sequences s = ( 5 ,. , T , ~ ) of real numbers with L Y ~ 5 H A ; the output sequence x + s + V , where V = ( VI, , y , ) is a sequence of independent and identically distributed Gaussian random variables with mean 0 and var...

This research was inspired by the need to increase the flexiblity and cost efficiency of a face recognition system by utilizing wireless sensor network for data transmission. Swarm intelligence is used to optimize routing in distributed time varying network by maintaining the required bit error rate for varied channel conditions while consuming minimal energy. Simulation shows the energy effici...

This research was inspired by the need of a flexible and cost effective biometric security system. The flexibility of the wireless sensor network makes it a natural choice for data transmission. Swarm intelligence is used to optimize routing in distributed time varying network. In this paper, swarm intelligence maintains the required BER for varied channel conditions while consuming minimal ene...

Given a contact network that changes over time (say, day vs night connectivity), and the SIS (susceptible/infected/susceptible, flu like) virus propagation model, what can we say about its epidemic threshold? That is, can we determine when a small infection will “take-off” and create an epidemic? Consequently then, which nodes should we immunize to prevent an epidemic? This is a very real probl...

—The emerging mobile applications including contact-based forwarding and online worm containment have put a heavy burden on opportunistic social networks (OSNs), the first goal is to develop an effective model that can reveal the hidden, important social features underlying the OSNs. This problem is especially challenging because of the time-varying network topology. Traditional time expanded ...