Information geometry theory of high-dimension space and application for speaker independent continuous digit speech recognition

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.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

A novel image restoration algorithm based on high-dimensional space geometry

A novel image restoration approach based on high-dimensional space geometry is proposed, which is quite different from the existing traditional image restoration techniques. It is based on the homeomorphisms and "Principle of Homology Continuity" (PHC), an image is mapped to a point in high-dimensional space. Begin with the original blurred image, we get two further blurred images, then the restored image can be obtained through the regressive curve derived from the three points which are mapped form the images. Experiments have proved the availability of this "blurred-blurred-restored" algorithm, and the comparison with the classical Wiener Filter approach is presented in final.

Comparison of space- and ground-grown Ce: Bi12SiO20 single crystals

Ce doped Bi12SiO20 single crystals were grown either on board of the Chinese Spacecraft-Shenzhou No.3 (SZ-3) or on the ground at the same conditions with the exception of microgravity. The surface morphology of crystals clearly showed significant differences between the space- and ground-grown portions. The space- and ground-grown crystals have been measured by X-ray rocking curve, Cc concentration distribution in growth direction, dislocation density, absorption spectrums. These results show that the compositional homogeneity and structural perfection of Ce doped crystal grown in space are obviously improved.

Space grown semi-insulating gallium arsenide single crystal and its application

Low noise field effect transistors and analogue switch integrated circuits (ICs) have been fabricated in semi-insulating gallium arsenide (SI-GaAs) wafers grown in space by direct ion-implantation. The electrical behaviors of the devices and the ICs have surpassed those fabricated in the terrestrially grown SI-GaAs wafers. The highest gain and the lowest noise of the transistors made from space-grown SI-GaAs wafers are 22.8 dB and 0.78 dB, respectively. The threshold back-gating voltage of the ICs made from space-grown SI-GaAs wafers is better than 8.5 V The con-elation between the characterizations of materials and devices is studied systematically. (C) 2002 COSPAR. Published by Elsevier Science Ltd. All rights reserved.

Absolute measurement of detector quantum efficiency using optical parametric down-conversion pumped by femtosecond laser pulses

Absolute measurement of detector quantum efficiency using optical parametric down-conversion has been extensively studied for the case of a continuous wave pump. In this paper, we have used the temporally and spatially correlated properties of the down-converted photon pairs generated in a nonlinear crystal pumped by a femtosecond laser pulse to perform an absolute measurement of detector quantum efficiency. The measured detector quantum efficiency is in excellent agreement with the measured value in the conventional way. A lens with a long focal length was adopted for efficiently increasing the intensity of the down-conversion entangled photon source.

Comparison of field effect transistor characteristics between space-grown and earth-grown gallium arsenide single crystal substrates

Semi-insulating gallium arsenide single crystal grown in space has been used in fabricating low noise field effect transistors and analog switch integrated circuits by the direct ion-implantation technique. All key electrical properties of these transistors and integrated circuits have surpassed those made from conventional earth-grown gallium arsenide. This result shows that device-grade space-grown semiconducting single crystal has surpassed the best terrestrial counterparts. (C) 2001 American Institute of Physics.

Semi-insulating GaAs grown in outer space

A semi-insulating GaAs single crystal ingot was grown in a recoverable satellite, within a specially designed pyrolytic boron nitride crucible, in a power-traveling furnace under microgravity. The characteristics of a compound semiconductor single crystal depends fundamentally on its stoichiometry, i.e. the ration of two types of atoms in the crystal. a practical technique for nondestructive and quantitative measuring stoichiometry in GaAs single crystal was used to analyze the space-grown GaAs single crystal. The distribution of stoichiometry in a GaAs wafer was measured for the first time. The electrical, optical and structural properties of the space-grown GaAs crystal were studied systematically, Device fabricating experiments prove that the quality of field effect transistors fabricated from direct ion-implantation in semi-insulating GaAs wafers has a close correlation with the crystal's stoichiometry. (C) 2000 Elsevier Science S.A. All rights reserved.

Structural properties of SI-GaAs grown in space

The structural properties of Semi-insulating gallium arsenide (SI-GaAs) crystal grown with power-travelling technique in space have been studied by double-crystal x-ray diffractometry and chemical etching. The quality of the crystal was first evaluated by x-ray rocking-curve method. The full width at half maximum of x-ray rocking curve in space-grown SI-GaAs is 9.4+/-0.08 are seconds. The average density of dislocations revealed by molten KOH is 2.0 X 10(4) cm(-2), and the highest density is 3.1 X 10(4) cm(-2). The stoichiometry in the single crystal grown in space is improved as well. Unfortunately, the rear of the ingot grown in space is polycrystalline owing to being out of control of power. (C) 1999 COSPAR. Published by Elsevier Science Ltd.

Outer space grown semi-insulating GaAs and its applications

GaAs single crystal has been grown in recoverable satellite. Hall measurements indicate that the GaAs shows semi-insulating behavior. The structural properties of the crystal have been improved obviously, and their uniformity has been improved as well. The stoichiometry and its distribution in space-grown GaAs are improved greatly compared with the GaAs single crystal grown terrestrially. The properties of integrated circuits made by direct ion-implantation on space-grown GaAs are better than those made on ground-grown materials. These results show that the stoichiometry in semi-insulating GaAs seriously affects the properties of related devices.

A novel image restoration approach based on point location in high-dimensional space geometry

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.

A face detection algorithm based on high dimensional space geometry

In this paper, a face detection algorithm which is based on high dimensional space geometry has been proposed. Then after the simulation experiment of Euclidean Distance and the introduced algorithm, it was theoretically analyzed and discussed that the proposed algorithm has apparently advantage over the Euclidean Distance. Furthermore, in our experiments in color images, the proposed algorithm even gives more surprises.

An algorithm of analysis tools on points distribution in high dimension space: The distance of a point and an infinite sub-space

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.

High-Dimensional Space Geometrical Informatics and its applications to image restoration

With a view to solve the problems in modern information science, we put forward a new subject named High-Dimensional Space Geometrical Informatics (HDSGI). It builds a bridge between information science and point distribution analysis in high-dimensional space. A good many experimental results certified the correctness and availability of the theory of HDSGI. The proposed method for image restoration is an instance of its application in signal processing. Using an iterative "further blurring-debluring-further blurring" algorithm, the deblured image could be obtained.

A novel image restoration algorithm based on high-dimensional space geometry

A novel image restoration approach based on high-dimensional space geometry is proposed, which is quite different from the existing traditional image restoration techniques. It is based on the homeomorphisms and "Principle of Homology Continuity" (PHC), an image is mapped to a point in high-dimensional space. Begin with the original blurred image, we get two further blurred images, then the restored image can be obtained through the regressive curve derived from the three points which are mapped form the images. Experiments have proved the availability of this "blurred-blurred-restored" algorithm, and the comparison with the classical Wiener Filter approach is presented in final.