163 resultados para Geometric pattern


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Time-resolved Faraday rotation spectroscopy is currently exploited as a powerful technique to probe spin dynamics in semiconductors. We propose here an all-optical approach to geometrically manipulate electron spin and to detect the geometric phase by this type of extremely sensitive experiment. The global nature of the geometric phase can make the quantum manipulation more stable, which may find interesting applications in quantum devices.

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We propose a nonadiabatic scheme for geometric quantum computation with trapped ions. By making use of the Aharonov-Anandan phase, the proposed scheme not only preserves the globally geometric nature in quantum computation, but also provides the advantage of nonadiabaticity that overcomes the problem of slow evolution in the existing adiabatic schemes. Moreover, the present scheme requires only two atomic levels in each ion, making it an appealing candidate for quantum computation.

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To overcome the isotropic directional emission of an ideal circular microdisk, two kinds of cylindrical mesa-like InGaAlP single quantum well (SQW) microdisks emitting at a visible red wavelength of 0.66 mu m have been fabricated. An anisotropic luminescence pattern was revealed by the microscopic fluorescence (FL) image. FL intensity, preferentially enhanced with twofold symmetry, appeared at the circumference of the InGaAlP SQW microdisks. Our results demonstrated that anisotropic radiation can be achieved by geometry shaping of the disks on the top view two-dimensional boundary slightly deformed from circular shape and/or on the side-view cross-section of the circular mesa by wet etching anisotropic undercut. (C) 2000 Elsevier Science Ltd. All rights reserved.

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In this paper, we propose a new scheme for omnidirectional object-recognition in free space. The proposed scheme divides above problem into several onmidirectional object-recognition with different depression angles. An onmidirectional object-recognition system with oblique observation directions based on a new recognition theory-Biomimetic Pattern Recognition (BPR) is discussed in detail. Based on it, we can get the size of training samples in the onmidirectional object-recognition system in free space. Omnidirection ally cognitive tests were done on various kinds of animal models of rather similar shapes. For the total 8400 tests, the correct recognition rate is 99.89%. The rejection rate is 0.11% and on the condition of zero error rates. Experimental results are presented to show that the proposed approach outperforms three types of SVMs with either a three degree polynomial kernel or a radial basis function kernel.

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In speaker-independent speech recognition, the disadvantage of the most diffused technology ( Hidden Markov Models) is not only the need of many more training samples, but also long train time requirement. This paper describes the use of Biomimetic Pattern Recognition (BPR) in recognizing some Mandarin Speech in a speaker-independent manner. The vocabulary of the system consists of 15 Chinese dish's names. Neural networks based on Multi-Weight Neuron (MWN) model are used to train and recognize the speech sounds. Experimental results are presented to show that the system, which can carry out real time recognition of the persons from different provinces speaking common Chinese speech, outperforms HMMs especially in the cases of samples of a finite size.

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Biomimetic pattern recognition has been proposed for several years, but the discussion of its neuron was not very wide and deep. In this paper, we propose a new more complex neuron named M-neuron and give the application in the last part of the paper.

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We studied the application of Biomimetic Pattern Recognition to speaker recognition. A speaker recognition neural network using network matching degree as criterion is proposed. It has been used in the system of text-dependent speaker recognition. Experimental results show that good effect could be obtained even with lesser samples. Furthermore, the misrecognition caused by untrained speakers occurring in testing could be controlled effectively. In addition, the basic idea "cognition" of Biomimetic Pattern Recognition results in no requirement of retraining the old system for enrolling new speakers.

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In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

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A novel in-plane bandgap energy controlling technique by ultra-low pressure (22 mbar) selective area growth (SAG) has been developed. To our knowledge, this is the lowest pressure condition during SAG process ever reported. In this work, high crystalline quality InGaAsP-InP MQWs with a photoluminescence (PL) full-width at half-maximum (FWHM) of less than 35meV are selectively grown on mask-patterned planar InP substrates by ultra-low pressure (22 mbar) metal-organic chemical vapor deposition (MOCVD). In order to study the uniformity of the MQWs grown in the selective area, novel tapered masks are designed and used. Through optimizing growth conditions, a wide wavelength shift of over 80 nm with a rather small mask width variation (0-30 mu m) is obtained. The mechanism of ultra-low pressure SAG is detailed by analyzing the effect of various mask designs and quantum well widths. This powerful technique is then applied to fabricate an electroabsorption-modulated laser (EML). Superior device characteristics are achieved, such as a low threshold current of 19mA and an output power of 7mW. (c) 2005 Elsevier B.V. All rights reserved.

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A novel geometric algorithm for blind image restoration is proposed in this paper, based on High-Dimensional Space Geometrical Informatics (HDSGI) theory. In this algorithm every image is considered as a point, and the location relationship of the points in high-dimensional space, i.e. the intrinsic relationship of images is analyzed. Then geometric technique of "blurring-blurring-deblurring" is adopted to get the deblurring images. Comparing with other existing algorithms like Wiener filter, super resolution image restoration etc., the experimental results show that the proposed algorithm could not only obtain better details of images but also reduces the computational complexity with less computing time. The novel algorithm probably shows a new direction for blind image restoration with promising perspective of applications.

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A 7.8-mu m surface emitting second-order distributed feedback quantum cascade laser (DFB QCL) structure with metallized surface grating is studied. The modal property of this structure is described by utilizing coupled-mode theory where the coupling coefficients are derived from exact Floquet-Bloch solutions of infinite periodic structure. Based on this theory, the influence of waveguide structure and grating topography as well as device length on the laser performance is numerically investigated. The optimized surface emitting second-order DFB QCL structure design exhibits a high surface outcoupling efficiency of 22% and a low threshold gain of 10 cm(-1). Using a pi phase-shift in the centre of the grating, a high-quality single-lobe far-field radiation pattern is obtained.

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LFC is a functional language based on recursive functions defined in context-free languages. In this paper, a new pattern matching algorithm for LFC is presented, which can represent a sequence of patterns as an integer by an encoding method. It is a rather simple method and produces efficient case-expressions for pattern matching definitions of LFC. The algorithm can also be used for other functional languages, but for nested patterns it may become complicated and further studies are needed.

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A new algorithm for compiling pattern matching is presented. Different from the traditional traversal-based approaches, it can represent a sequence of patterns as an integer by an encoding method and translate equations into case-expressions. The algorithm is simple to implement, and efficient for a kind of patterns, i.e. simple and dense patterns. This method can be complementary to traditional approaches.