An efficient and accurate model of a distributed feedback laser integrated with an electroabsorption modulator is established. Good agreement between the calculated and measured results for the time-resolved chirp is achieved.
A novel surface roughness optical fiber sensor is presented. It consists of a light emitting diode source, an Y-tap, a probe made up of self-focusing optical fiber, a photo- detector setup, and a fuzzy system. Its principle is based on the intensity-modulated light from an object surface to be measured. The fuzzy algorithm was used to treat the data obtained from photo-detector setup. Since the fuzzy algorithm can map input and output perfectly, the measure accuracy was improved and the measure range was expanded.
We propose a new Gibbs sampling algorithm, the soft- criterion acceptance algorithm, and use it for the texture synthesis. The new algorithm combines the advantages of the ICM algorithm in computations and of the algorithm of simulated annealing (SA) in global convergence. As a result, it is computationally efficient in comparison with the Gibbs sampler by S. Geman and D. Geman. The key idea is that the difference of the maximum and minimum of the energy functions is used to construct a soft criterion for updating each pixel value in a probabilistic acceptance fashion that is similar to the SA. The algorithm is verified by computational experiments.
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