236 resultados para interference pattern


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Effect of surface structures upon ultrathin film interference fringes generated from extremely thin films or epitaxial layers grown on semiconductor wafers has been studied. Since dark regions of fringes correspond to the places where the thin films are destroyed or absent, the fringes are investigated to detect uneven surfaces with undesired structures. Therefore, surface microstructures can be detected and characterized effectively by the modification of the fringes.

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Ultrathin single quantum well (about one monolayer) grown on GaAs(001) substrate with GaAs cap layer has been studied by high resolution x-ray diffractometer on a beamline of the Beijing Synchrotron Radiation Facility. The interference fringes on both sides of the GaAs(004) Bragg peak are asymmetric and a range of weak fringes in the higher angle side of the Bragg peak is observed. The simulated results by using the kinematical diffraction method shows that the weak fringe range appears in the higher angle side when the phase shift introduced by the single quantum well is very slightly smaller than m pi (m:integer), and vice versa. After introducing a reasonable model of single quantum well, the simulated pattern is in good agreement with the experiment. (C) 1996 American Institute of Physics.

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Quantum interference properties of GaAs/AlGaAs symmetric double quantum wells were investigated in a magnetic field parallel to heterointerfaces at 1.9 K. For two types of samples used in our experiments, two GaAs quantum wells with the same width of 60 Angstrom are separated by an AlGaAs barrier layer of 120 Angstrom and 20 degrees thick, respectively. The channels with the length of 2 mu m are defined by alloyed ohmic contacts. The conductance oscillation as a function of the magnetic flux Phi(= B/s) was observed and oscillation period is approximately equal to h/e. The results are in agreement with the theoretical expectation of the Aharonov-Bohm effect. Conductance oscillations are apparent slightly in the samples with a thinner AlGaAs barrier.

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A silicon-on-insulator based channel-shifted multimode interference coupler is designed and fabricated. A two dimensional beam propagation method is used to analyze the dependence of coupler′s performances on the width and length of the multimode waveguide. The device fabricated has a power shift ratio of 73 and an excess loss of about 2.2 dB. An enhancement of fabrication accuracies could further improve the coupler performances.

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A novel structure of MMI coupler with different background refractive index has been designed. With stronger optical confinement in multimode waveguides, more guided modes are excited to improve imaging quality. Two-dimensional finite difference beam propagation method (2-D FDBPM) was used to simulate this new structure and had proven that its imaging quality, in terms of power uniformity and excess loss, is much better than conventional structure. This structure can be applied in SOI rib waveguides by deep etching method.

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The temperature dependence of characteristics for multimode interference (MMI) based 3-dB coupler in silicon-on-insulator is analyzed, which originates from the relatively high thermo-optic coefficient of silicon. For restricted interference 3-dB MMI coupler, the output power uniformity is ideally 0 at room temperature and becomes 0. 32 dB when temperature rises up to 550 K. For symmetric interference 3-dB MMI coupler, the power uniformity keeps ideally 0 due to its intrinsic symmetric interference mechanism. With the temperature rising, the excess loss of the both devices increases. The performance deterioration due to temperature variety is more obvious to restricted interference MMI 3-dB coupler, comparing with that of symmetric interference MMI 3-dB coupler.

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A new method of face recognition, based on Biomimetic Pattern Recognition and Multi-Weights Neuron Network, had been proposed. A model for face recognition that is based on Biomimetic Pattern Recognition had been discussed, and a new method of facial feature extraction also had been introduced. The results of experiments with BPR and K-Nearest Neighbor Rules showed that the method based on BPR can eliminate the error recognition of the samples of the types that not be trained, the correct rate is also enhanced.

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A new theoretical model of Pattern Recognition principles was proposed, which is based on "matter cognition" instead of "matter classification" in traditional statistical Pattern Recognition. This new model is closer to the function of human being, rather than traditional statistical Pattern Recognition using "optimal separating" as its main principle. So the new model of Pattern Recognition is called the Biomimetic Pattern Recognition (BPR)(1). Its mathematical basis is placed on topological analysis of the sample set in the high dimensional feature space. Therefore, it is also called the Topological Pattern Recognition (TPR). The fundamental idea of this model is based on the fact of the continuity in the feature space of any one of the certain kinds of samples. We experimented with the Biomimetic Pattern Recognition (BPR) by using artificial neural networks, which act through covering the high dimensional geometrical distribution of the sample set in the feature space. Onmidirectionally cognitive tests were done on various kinds of animal and vehicle models of rather similar shapes. For the total 8800 tests, the correct recognition rate is 99.87%. The rejection rate is 0.13% and on the condition of zero error rates, the correct rate of BPR was much better than that of RBF-SVM.

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Silicon-on insulator (SOI) is an attractive platform for the fabrication of optoelectronic integrated circuit. Thin cladding layers (< 1.0m) can be used in SOI waveguide due to the large index step between Si and SiO2, making them compatible with the VLSI technology. Here we demonstrate the fabrication of 1 x 4 and 2 x 2 multimode interference (MMI) coupler based on SOI technology. Performances of the devices are analyzed. The minimum excess loss of the devices is about 1.8dB. The devices show uniform power distribution.

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An improved BP algorithm for pattern recognition is proposed in this paper. By a function substitution for error measure, it resolves the inconsistency of BP algorithm for pattern recognition problems, i.e. the quadratic error is not sensitive to whether the training pattern is recognized correctly or not. Trained by this new method, the computer simulation result shows that the convergence speed is increased to treble and performance of the network is better than conventional BP algorithm with momentum and adaptive step size.

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A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.