2 resultados para normal-mode analysis

em Digital Commons - Michigan Tech


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We investigate the operation of optical isolators based on magneto-optics waveguide arrays beyond the coupled mode analysis. Semi-vectorial beam propagation simulations demonstrate that evanescent tail coupling and the effects of radiation are responsible for degrading the device’s performance. Our analysis suggests that these effects can be mitigated when the array size is scaled up. In addition, we propose the use of radiation blockers in order to offset some of these effects, and we show that they provide a dramatic improvement in performance. Finally, we also study the robustness of the system with respect to fabrication tolerances using the coupled mode theory. We show that small, random variations in the system’s parameters tend to average out as the number of optical guiding channels increases.

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In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption. As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior distribution, we propose an efficient Gibbs-type with Metropolis- Hastings sampling algorithm for posterior Bayesian inference. Thereafter, following the idea of [1], we consider the problems of the single and multiple change-point detections. The performance of the proposed procedures is illustrated and analyzed by simulation studies. A real application to the closing price data of U.S. stock market has been analyzed for illustrative purposes.