Er3+-doped glass-polymer composite thin films fabricated using combinatorial pulsed laser deposition

Siloxane Polymer exhibits low loss in the 800-1500 nm range which varies between 0.01 and 0.66 dB cm1. It is for such low loss the material is one of the most promising candidates in the application of engineering passive and active optical devices [1, 2]. However, current polymer fabrication techniques do not provide a methodology which allows high structurally solubility of Er3+ ions in siloxane matrix. To address this problem, Yang et al.[3] demonstrated a channel waveguide amplifier with Nd 3+-complex doped polymer, whilst Wong and co-workers[4] employed Yb3+ and Er3+ co-doped polymer hosts for increasing the gain. In some recent research we demonstrated pulsed laser deposition of Er-doped tellurite glass thin films on siloxane polymer coated silica substrates[5]. Here an alternative methodology for multilayer polymer-glass composite thin films using Er3+ - Yb3+ co-doped phosphate modified tellurite (PT) glass and siloxane polymer is proposed by adopting combinatorial pulsed laser deposition (PLD). © 2011 IEEE.

The cross-entropy method for blind multiuser detection

We consider the problem of blind multiuser detection. We adopt a Bayesian approach where unknown parameters are considered random and integrated out. Computing the maximum a posteriori estimate of the input data sequence requires solving a combinatorial optimization problem. We propose here to apply the Cross-Entropy method recently introduced by Rubinstein. The performance of cross-entropy is compared to Markov chain Monte Carlo. For similar Bit Error Rate performance, we demonstrate that Cross-Entropy outperforms a generic Markov chain Monte Carlo method in terms of operation time.

A general design method for electric machines using magnetic circuit model considering the flux saturation problem

This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.

Rigorous finite-time guarantees for optimization on continuous domains by simulated annealing

Simulated annealing is a popular method for approaching the solution of a global optimization problem. Existing results on its performance apply to discrete combinatorial optimization where the optimization variables can assume only a finite set of possible values. We introduce a new general formulation of simulated annealing which allows one to guarantee finite-time performance in the optimization of functions of continuous variables. The results hold universally for any optimization problem on a bounded domain and establish a connection between simulated annealing and up-to-date theory of convergence of Markov chain Monte Carlo methods on continuous domains. This work is inspired by the concept of finite-time learning with known accuracy and confidence developed in statistical learning theory.