154 resultados para Line geometry.
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A novel approach for multi-dimension signals processing, that is multi-weight neural network based on high dimensional geometry theory, is proposed. With this theory, the geometry algorithm for building the multi-weight neuron is mentioned. To illustrate the advantage of the novel approach, a Chinese speech emotion recognition experiment has been done. From this experiment, the human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. And the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. Compared with traditional GSVM model, the new method has its superiority. It is noted that this method has significant values for researches and applications henceforth.
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We investigate the lifetime distribution functions of spontaneous emission from line antennas embedded in finite-size two-dimensional 12-fold quasi-periodic photonic crystals. Our calculations indicate that two-dimensional quasi-periodic crystals lead to the coexistence of both accelerated and inhibited decay processes. The decay behaviors of line antennas are drastically changed as the locations of the antennas are varied from the center to the edge in quasi-periodic photonic crystals and the location of transition frequency is varied.
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A method for fabrication of long-wavelength narrow line-width InGaAs resonant cavity enhanced (RCE) photodetectors in a silicon substrate operating at the wavelength range of 1.3-1.6 mu m has been developed. A full width at half maximum (FWHM) of 0.7 nm and a peak responsivity of 0. 16 A/W at the resonance wavelength of 1.55 mu m have been accomplished by using a thick InP layer as part of the resonant cavity. The effects of roughness and tilt of the InP layer surface, and its free carrier absorption, as well as the thickness deviation of the mirror pair on the resonance wavelength shift and the peak quantum efficiency of the RCE photodetectors are analyzed in detail, and approaches for minimizing them toward superior performance are suggested. (C) 2007 Elsevier B.V. All rights reserved.
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Studies on learning problems from geometry perspective have attracted an ever increasing attention in machine learning, leaded by achievements on information geometry. This paper proposes a different geometrical learning from the perspective of high-dimensional descriptive geometry. Geometrical properties of high-dimensional structures underlying a set of samples are learned via successive projections from the higher dimension to the lower dimension until two-dimensional Euclidean plane, under guidance of the established properties and theorems in high-dimensional descriptive geometry. Specifically, we introduce a hyper sausage like geometry shape for learning samples and provides a geometrical learning algorithm for specifying the hyper sausage shapes, which is then applied to biomimetic pattern recognition. Experimental results are presented to show that the proposed approach outperforms three types of support vector machines with either a three degree polynomial kernel or a radial basis function kernel, especially in the cases of high-dimensional samples of a finite size. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
The authors calculate the lifetime distribution functions of spontaneous emission from infinite line antennas embedded in two-dimensional disordered photonic crystals with finite size. The calculations indicate the coexistence of both accelerated and inhibited decay processes in disordered photonic crystals with finite size. The decay behavior of the spontaneous emission from infinite line antennas changes significantly by varying factors such as the line antennas' positions in the disordered photonic crystal, the shape of the crystal, the filling fraction, and the dielectric constant. Moreover, the authors analyze the effect of the degree of disorder on spontaneous emission. (c) 2007 American Institute of Physics.
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A new method to measure reciprocal four-port structures, using a 16-term error model, is presented. The measurement is based on 5 two-port calibration standards connected to two of the ports, while the network analyzer is connected to the two remaining ports. Least-squares-fit data reduction techniques are used to lower error sensitivity. The effect of connectors is deembedded using closed-form equations. (C) 2007 Wiley Periodicals, Inc.
Resumo:
In practical situations, the causes of image blurring are often undiscovered or difficult to get known. However, traditional methods usually assume the knowledge of the blur has been known prior to the restoring process, which are not practicable for blind image restoration. A new method proposed in this paper aims exactly at blind image restoration. The restoration process is transformed into a problem of point distribution analysis in high-dimensional space. Experiments have proved that the restoration could be achieved using this method without re-knowledge of the image blur. In addition, the algorithm guarantees to be convergent and has simple computation.
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We present fabrication and experimental measurement of a series of photonic crystal waveguides. The complete devices consist of an injector taper down from 3 mu m into a triangular-lattice air-hole single-line-defect waveguide with lattice constant from 410nm to 470nm and normalized radius 0.31. We fabricate these devices on a siliconon-insulator substrate and characterize them using a tunable laser source over a wavelength range from 1510nm to 1640nm. A sharp attenuation at photonic crystal waveguide mode edge is observed for most structures. The edge of guided band is shifted about 30nm with the 10nm increase of the lattice constant. We obtain high-efficiency light propagation and broad flat spectrum response of the photonic crystal waveguides.
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地址: Chinese Acad Sci, Inst Semicond, State Key Lab Integrated Optoelect, Beijing 100083, Peoples R China
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The performance of the current sensor in power equipment may become worse affected by the environment. In this paper, based on ICA, we propose a method for on-line verification of the phase difference of the current sensor. However, not all source components are mutually independent in our application. In order to get an exact result, we have proposed a relative likelihood index to choose an optimal result from different runs. The index is based on the maximum likelihood evaluation theory and the independent subspace analysis. The feasibility of our method has been confirmed by experimental results.
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Because of information digitalization and the correspondence of digits and the coordinates, Information Science and high-dimensional space have consanguineous relations. With the transforming from the information issues to the point analysis in high-dimensional space, we proposed a novel computational theory, named High dimensional imagery geometry (HDIG). Some computational algorithms of HDIG have been realized using software, and how to combine with groups of simple operators in some 2D planes to implement the geometrical computations in high-dimensional space is demonstrated in this paper. As the applications, two kinds of experiments of HDIG, which are blurred image restoration and pattern recognition ones, are given, and the results are satisfying.
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In the light of descriptive geometry and notions in set theory, this paper re-defines the basic elements in space such as curve and surface and so on, presents some fundamental notions with respect to the point cover based on the High-dimension space (HDS) point covering theory, finally takes points from mapping part of speech signals to HDS, so as to analyze distribution information of these speech points in HDS, and various geometric covering objects for speech points and their relationship. Besides, this paper also proposes a new algorithm for speaker independent continuous digit speech recognition based on the HDS point dynamic searching theory without end-points detection and segmentation. First from the different digit syllables in real continuous digit speech, we establish the covering area in feature space for continuous speech. During recognition, we make use of the point covering dynamic searching theory in HDS to do recognition, and then get the satisfying recognized results. At last, compared to HMM (Hidden Markov models)-based method, from the development trend of the comparing results, as sample amount increasing, the difference of recognition rate between two methods will decrease slowly, while sample amount approaching to be very large, two recognition rates all close to 100% little by little. As seen from the results, the recognition rate of HDS point covering method is higher than that of in HMM (Hidden Markov models) based method, because, the point covering describes the morphological distribution for speech in HDS, whereas HMM-based method is only a probability distribution, whose accuracy is certainly inferior to point covering.
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In this paper, a novel algorithm for removing facial makeup disturbances as a face detection preprocess based on high dimensional imaginal geometry is proposed. After simulation and practical application experiments, the algorithm is theoretically analyzed. Its apparent effect of removing facial makeup and the advantages of face detection with this pre-process over face detection without it are discussed. Furthermore, in our experiments with color images, the proposed algorithm even gives some surprises.
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In this paper, a novel approach for mandarin speech emotion recognition, that is mandarin speech emotion recognition based on high dimensional geometry theory, is proposed. The human emotions are classified into 6 archetypal classes: fear, anger, happiness, sadness, surprise and disgust. According to the characteristics of these emotional speech signals, the amplitude, pitch frequency and formant are used as the feature parameters for speech emotion recognition. The new method called high dimensional geometry theory is applied for recognition. Compared with traditional GSVM model, the new method has some advantages. It is noted that this method has significant values for researches and applications henceforth.
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In this paper, we study a problem of geometric inequalities for a Multi-degree of Freedom Neurons. Some new geometric inequalities for a Multi-degree of Freedom Neurons are established. As special cases, some known inequalities are deduced.