977 resultados para best proximity point


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Compared with the ordinary adaptive filter, the variable-length adaptive filter is more efficient (including smaller., lower power consumption and higher computational complexity output SNR) because of its tap-length learning algorithm, which is able to dynamically adapt its tap-length to the optimal tap-length that best balances the complexity and the performance of the adaptive filter. Among existing tap-length algorithms, the LMS-style Variable Tap-Length Algorithm (also called Fractional Tap-Length Algorithm or FT Algorithm) proposed by Y.Gong has the best performance because it has the fastest convergence rates and best stability. However, in some cases its performance deteriorates dramatically. To solve this problem, we first analyze the FT algorithm and point out some of its defects. Second, we propose a new FT algorithm called 'VSLMS' (Variable Step-size LMS) Style Tap-Length Learning Algorithm, which not only uses the concept of FT but also introduces a new concept of adaptive convergence slope. With this improvement the new FT algorithm has even faster convergence rates and better stability. Finally, we offer computer simulations to verify this improvement.

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The goal of image restoration is to restore the original clear image from the existing blurred image without distortion as possible. A novel approach based on point location in high-dimensional space geometry method is proposed, which is quite different from the thought ways of existing traditional image restoration approaches. It is based on the high-dimensional space geometry method, which derives from the fact of the Principle of Homology-Continuity (PHC). Begin with the original blurred image, we get two further blurred images. Through the regressive deducing curve fitted by these three images, the first iterative deblured image could be obtained. This iterative "blurring-debluring-blurring" process is performed till reach the deblured image. Experiments have proved the availability of the proposed approach and achieved not only common image restoration but also blind image restoration which represents the majority of real problems.

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This paper discusses the algorithm on the distance from a point and an infinite sub-space in high dimensional space With the development of Information Geometry([1]), the analysis tools of points distribution in high dimension space, as a measure of calculability, draw more attention of experts of pattern recognition. By the assistance of these tools, Geometrical properties of sets of samples in high-dimensional structures are studied, under guidance of the established properties and theorems in high-dimensional geometry.

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In this paper, we focus on the dipole mode of the two-dimensional (2D) photonic crystal (PC) single point defect cavity (SPDC) lasers and we report the fabrication and characterization of 2D PC SPDC lasers with the structure of adjusted innermost air holes. The photonic band and cavity Q factors are simulated by means of plane wave expansion (PWE) and finite-difference time-domain (FDTD), respectively. In order to improve the optical confinement of the SPDC, the diameter of the innermost holes was adjusted. Different lasing performances are observed experimentally. The experimental results agree with the theoretical prediction very well. (c) 2006 Elsevier B.V. All rights reserved.

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An important concept proposed in the early stage of robot path planning field is the shrinking of the robot to a point and meanwhile expanding of the obstacles in the workspace as a set of new obstacles. The resulting grown obstacles are called the Configuration Space (Cspace) obstacles. The find-path problem is then transformed into that of finding a collision free path for a point robot among the Cspace obstacles. However, the research experiences obtained so far have shown that the calculation of the Cspace obstacles is very hard work when the following situations occur: 1. both the robot and obstacles are not polygons and 2. the robot is allowed to rotate. This situation is even worse when the robot and obstacles are three dimensional (3D) objects with various shapes. Obviously a direct path planning approach without the calculation of the Cspace obstacles is strongly needed. This paper presents such a new real-time robot path planning approach which, to the best of our knowledge, is the first one in the robotic community. The fundamental ideas are the utilization of inequality and optimization technique. Simulation results have been presented to show its merits.

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Short-range correlations of two-dimensional electrons in a strong magnetic field are shown to be triangular in nature well below half-filling, but honeycomb well above half-filling. The half-filling point is thus proposed, and qualitatively confirmed by three-body correlation calculations, to be a new type of disorder point where short-range correlations change character. A wavefunction study also suggests that nodes become unbound at half-filling. Evidence for incompressibility but deformability of the half-filling state earlier suggested by Fano, Ortolani and Tosatti, is also presented and found to be in agreement with recent experiments.