The issue of Quality of Service (QoS) performance analysis in packet switched networks has drawn a lot of attention in the networking community in recent years. There is a lot of work including an elegant theory under the name of network calculus focusing on analysis of deterministic worst case QoS performance bounds. In the meantime, other researchers have studied the stochastic QoS performanc...

This research is to develop a new form of stochastic network calculus for queuing system performance guarantees by making use of the Legendre transform at the sample-path level. A symmetrical formulation is resulted in through separate modeling of traffic flows and service capacities. Performance measures at single nodes and the service capacities of tandem systems are explicitly bounded at the...

The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of neural systems in the brain. In principle there exists a powerful computational framework for stochastic computations, probabilistic inference by s...

Using limited assets, an interdictor attempts to destroy parts of a capacitated network through which an adversary will subsequently maximize flow. We formulate and solve a stochastic version of the interdictor’s problem: Minimize the expected maximum flow through the network when interdiction successes are binary random variables. Extensions are made to handle uncertain arc capacities and othe...

High dimensional sequential data exhibits complex structure, a successful generative model for such data must involve highly dependent, structured variables. Thus it is desired or even necessary to model correlations and dependencies between the multiple input, output variables and latent variables in such scenario. To achieve this goal, we introduce Variational Structured Stochastic Network(VS...

vii

Oscillatory neural activity within the gamma band (25-90 Hz) is generally thought to be able to provide a timing signal for harmonizing neural computations across different brain regions. Using time-frequency analyses of the dynamics of gamma-band activity in the local field potentials recorded from monkey primary visual cortex, we found identical temporal characteristics of gamma activity in b...

Substantial work has applied stochastic techniques to network reliability models. These techniques can estimate risk, variance and uncertainty values. Unfortunately, these models do not address the issues of revenues, return on investment, or the time-value of money. To address these issues, we have developed an Economic Reliability Analysis [ERA] framework at the University of Virginia that fu...

We analyse the effects of extrinsic noise on traveling waves of visual perception in a competitive neural field model of binocular rivalry. The model consists of two one-dimensional excitatory neural fields, whose activity variables represent the responses to left-eye and right-eye stimuli, respectively. The two networks mutually inhibit each other, and slow adaptation is incorporated into the ...

Stochastic neural networks for global optimization are usually built by introducing random uctuations into the network. A natural method is to use stochastic weights rather than stochastic activation functions. We propose a new model in which each neuron has very simple functionality but all the weights are stochastic. It is shown that the stationary distribution of the network uniquely exists ...