This paper describes a graph-spectral method for path estimation. Our aim is to find a maximum probability path through a lattice of pixel sites. We characterise the path recovery problem using a site transition matrix. A graph-spectral analysis of the transition matrix reveals how the maximum probability path can be located using an eigenvector of the associated normalised affinity matrix. We ...

We analyze the Dicke model at zero temperature by matrix diagonalization to determine the entanglement in the ground state. In the infinite system limit the mean field approximation predicts a quantum phase transition from a non-interacting state to a BoseEinstein condensate at a threshold coupling. We show that in a finite system the spin part of the ground state is a bipartite entangled state...

Excited state dynamics of S2 and S1 states for a series of TPM dyes, pyrogallol red (PGR), bromopyrogallol red (Br-PGR) and aurin tricarboxylic acid (ATC), have been monitored by using ultrafast transient absorption and fluorescence up-conversion techniques. Optical absorption studies indicate that all the TPM dyes exist as keto-enol tautomers depending upon the pH of the solution. Interestingl...

This paper considers a queuing system with finite buffer, constant main MAP flow, and an additional periodic (non-periodic) Poisson piecewise-constant flow of customers. The eigenvalues the probability translation matrix Kolmogorov input intensities is analyzed. definition transition mode time based on analysis determinant introduced for first time. An analytical solution to equation piecewise ...

every digital transmission system requires frame alignment. it is necessary to identify the varius signal componets and to bring receiver into phase with respect to the transmission format so that the digits can be properly assembled for demultiplexing. fast and reliable frame alignmant is important, and therefore has been a subject for study. this paper a comprehensive analysis of frame alignm...

The analysis of spontaneous resting state neuronal activity is assumed to give insight into the brain function. One noninvasive technique to study resting state activity is electroencephalography (EEG) with a subsequent microstate analysis. This technique reduces the recorded EEG signal to a sequence of prototypical topographical maps, which is hypothesized to capture important spatio-temporal ...

For our purposes, a Markov chain is a (finite or countable) collection of states S and transition probabilities pij, where i, j ∈ S. We write P = [pij] for the matrix of transition probabilities. Elements of S can be interpreted as various possible states of whatever system we are interested in studying, and pij represents the probability that the system is in state j at time n+ 1, if it is sta...

A hidden Markov model (HMM) defines a joint probability distribution of a series of observations xt and hidden states zt for t = 1, . . . , T . We use x1:T and z1:T to refer to the full sequence of observations and states respectively. In a HMM the prior on the state sequence is assumed to satisfy the Markov property, which is to say that the probability of each state zt depends only on the pre...

This paper addresses the stabilization problem for single-input Markov jump linear systems via modedependent quantized state feedback. Given a measure of quantization coarseness, a mode-dependent logarithmic quantizer and amode-dependent linear state feedback law can achieve optimal coarseness for mean square quadratic stabilization of a Markov jump linear system, similar to existing results fo...