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Robust Design of Slow-Light Tapers in Periodic Waveguides
robust optimization PDE-constrained optimization shape optimization coupling taper
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2015/7/9
This paper concerns the design of tapers for coupling power between uniform and slow-light periodic waveguides. New optimization methods are described for designing robust tapers, which not only perfo...
Robust Optimization of Adiabatic Tapers for Coupling to Slow-Light Photonic-Crystal Waveguides
Computational electromagnetic methods Optoelectronics Photonic crystal waveguides Photonic integrated circuits
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2015/7/9
We investigate the design of taper structures for coupling to slow-light modes of various photonic-crystal waveguides while taking into account parameter uncertainties inherent in practical fabricatio...
A parameter estimation method based on random slow manifolds
Parameter estimation Slow-fast system Random slow manifold Quantifying uncer-tainty Numerical optimization
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2013/5/2
A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the syste...
Slow convergence to normality: and Edgeworth expansion without third moment
Slow convergence to normality Edgeworth expansion without third moment
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2009/9/22
Let F be a non-lattice distribution function which lies in
the domain of attraction of a normal distribution. Exact uniform convergence
rates are obtained for the convergence of the normalized parti...
A central limit theorem for strictly stationary sequences in terms of slow variation in the limit
A central limit theorem strictly stationary sequences terms of slow variation
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2009/9/22
For strictly stationary random sequences satisfying the
"minimal" dependence condition, necessary and sufficient conditions
for the weak convergence to the normal law in terms of slow variation
in ...
How to Combine Fast Heuristic Markov Chain Monte Carlo with Slow Exact Sampling
Confidence interval Exact sampling Markov Chain Monte Carlo
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2009/5/4
Given a probability law $pi$ on a set S and a function $g : S rightarrow R$, suppose one wants to estimate the mean $bar{g} = int g dpi$. The Markov Chain Monte Carlo method consists of inventing and ...