A pure silica microstructured optical fiber(MOF) with seven dual cores is designed for chromatic dispersion compensation by a finite difference frequency domain(FDFD) method with a perfect matched layer(PML) boundary condition. The multi-core structure fiber is presented for the first time. The negative chromatic dispersion peak value of the designed microstructured fiber is -4500ps/nm.km and the full width at half maximum (FWHM) is evaluated at 12nm. Furthermore the effective area of the inner core fundamental mode can reach 65mm2 at 1550nm wavelength, which is three times that of a conventional dispersion compensating fiber (DCF).
Based on a compact 2-D Finite-Difference Time-Domain(FDTD) method, We study the effect of imperfection of transverse periodicity on the leakage loss in photonic crystal fibers(PCFs). Random fluctuations of holes radius and position in PCFs are introduced to analyze their effect on the guiding ability.
In this work, methods of design and fabrication of photonic bandgap structures (PBG) and photonic crystal waveguides based on SOI (silicon on insulator) are presented. In theory, a method that incorporates the plane wave expansion (PWE) method based on supercell with the finite-difference time-domain (FDTD) method with a perfectly matched layer (PML) boundary condition has been investigated. At first, PWE simulation will present a band structure. Then according to the band structure, FDTD tool can simulate a light propagation and can obtain optimized parameters easily. With the method, several photonic crystal devices suitable for 248nm Deep UV lithography and 0.18um ion-beam etching are designed and fabricated.
This paper proposes an algorithm for relevance feedback in region-based image retrieval systems. In region-based image retrieval systems one image usually represented by many regions, each region is represented by a feature vector. Because traditional region-based feedback algorithms are based on the one-vector model, it is hard to directly use past feedback algorithms to a region-based image retrieval system. In this paper we propose a novel feedback algorithm using clustering among regions in all feedback images on region-based image retrieval systems. All regions in one image are divided into two parts: the foreground regions and the background regions based on the feedback images. Here foreground regions stand for the common property of all feedback images, which can be viewed as being of one semantic category. The others are background regions, which may stand for different semantic categories. During feedback, we treat the two kinds of regions with different manner. Experimental results show that using such algorithm improves the retrieval performance of region based image system.
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