Performance analysis of very-small-aperture lasers

The fabrication of very-small-aperture lasers is demonstrated, and their performance is analyzed. Because of strong optical feedback caused by a gold film on the front facet of the laser, its behavior changes: The threshold current decreases, the density of light inside the laser diode and the redshift effect of the spectra are enhanced, and the laser diode's lifetime is shorter than that of common laser diodes with large driving current. (c) 2005 Optical Society of America

Effect of fabrication conditions on I-V properties for ZnO varistor with high concentration additives by sol-gel technique

Polycrystalline nano-grain-boundary multi-doping ZnO-based nonlinear varistors with higher concentration additives have been fabricated by sol-gel and standard solid-state reaction method, of which the best sample has a very high threshold voltage of E-b = 3300 V/mm. The effect of sintering processes, sintering temperature and sintering time, and that of additive concentration of Bi2O3 on E-b of the samples are systematically investigated. The results show that the great merit of sol-gel method is its high threshold voltage obtained by a lower sintering temperature than the solid-state reaction method. The present work also shows that five phases including solid-state sintering, rich Bi liquid phase formation and ZnO as well as other additive dissolution, ZnO grain growth, the secondary phase sufficient formation and evolution have been experienced at different sintering temperatures. The hole type defect and nonhomogeneity of the microstructure will lead to the decrease of threshold voltage, i.e., the grain size and the homogeneity of the material will be important factors and directly affect the characteristic of the varistor. The sintering characteristic and the influence of Bi2O3 content on the threshold voltage are also discussed. (c) 2004 Elsevier B.V. All rights reserved.

Manifold covering theory in biomimetic pattern recognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite manifold covering in biomimetic pattern recognition, and study its property. Furthermore, we propose this manifold covering algorithm based on Biomimetic Pattern Recognition. At last, the experimental results for face recognition demonstrates that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Improved performance in organic light emitting diodes with a mixed electron donor-acceptor film involved in hole injection

Organic light emitting diodes using a mixed layer of electron acceptor 3, 4, 9, 10 perylenetetracarboxylic dianhydride and electron donor copper phthalocyanine (PTCDA:CuPc) on indium tin oxide (ITO) anodes were fabricated. The device properties were found to be strongly dependent on the thickness of the PTCDA:CuPc film: both the power efficiency and the driving voltage of the device were optimized with a thickness of PTCDA:CuPc ranging from 10 to 20 nm. As compared to the conventional ITO/CuPc hole injection structure, the ITO/PTCDA:CuPc hole injection structure could remarkably enhance both the luminance and the power efficiencies of devices. A mechanism of static-induced, very efficient hole-electron pairs generation in mixed PTCDA:CuPc films was proposed to explain the experimental phenomena. The structural and optical properties of PTCDA:CuPc film were examined as well. (c) 2007 American Institute of Physics.

Organic light emitting diodes with an organic acceptor/donor interface involved in hole injection

Organic light emitting diodes with an interface of organic acceptor 3-, 4-, 9-, 10-perylenetetracarboxylic dianhydride (PTCDA) and donor copper phthalocyanine (CuPc) involved in hole injection are fabricated. As compared to the conventional device using a 5 nm CuPc hole injection layer, the device using an interface of 10 nm PTCDA and 5 rim CuPc layers shows much lower operating voltage with an increase of about 46% in the maximum power efficiency. The enhanced device performance is attributed to the efficient hole generation at the PTCDA/CuPc interface. This study provides a new way of designing hole injection.

Photoluminescence from Er-doped Si-in-SiNx thin films

Photoluminescence from Er3+-implanted Si-in-SiN, films emitting efficiently visible light were investigated. A Stark structure in the Er3+ photoluminescence spectrum was observed at room temperature, which reveals more than one site symmetry for the Er3+-centers in the Si-in-SiN, matrix. The correlation between the visible photoluminescence from the silicon nanoparticles and the 1.54 mu m emission from the Er3+-centers was discussed. (c) 2006 Elsevier B.V. All rights reserved.

Blind image restoration based on the theory of high-dimensional space geometry

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.

Design and characteristics of quantum cascade laser-based CO detection system

National High Technology Research and Development Program of China 2007AA03Z112；Program of Ministry of Education of China 20060183030；Program of Jilin Provincial Science and Technology Department of China 20070709；Program of Bureau of Science and Technology of Changchun City 2007107

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.

Mandarin speech emotion recognition based on high dimensional geometry theory

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.

Viruses' complete genomes classification based on geometrical learning

In this paper, we proposed a method of classification for viruses' complete genomes based on graph geometrical theory in order to viruses classification. Firstly, a model of triangular geometrical graph was put forward, and then constructed feature-space-samples-graphs for classes of viruses' complete genomes in feature space after feature extraction and normalization. Finally, we studied an algorithm for classification of viruses' complete genomes based on feature-space-samples-graphs. Compared with the BLAST algorithm, experiments prove its efficiency.

Research on continuous speech recognition with small vocabulary based on biomimetic pattern recognition

Based on biomimetic pattern recognition theory, we proposed a novel speaker-independent continuous speech keyword-spotting algorithm. Without endpoint detection and division, we can get the minimum distance curve between continuous speech samples and every keyword-training net through the dynamic searching to the feature-extracted continuous speech. Then we can count the number of the keywords by investigating the vale-value and the numbers of the vales in the curve. Experiments of small vocabulary continuous speech with various speaking rate have got good recognition results and proved the validity of the algorithm.

Geometry property of multi-degree of freedom neurons

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.

Cognitive models in biomimetic pattern cognition

We describe a new model which is based on the concept of cognizing theory. The method identifies subsets of the data which are embedded in arbitrary oriented lower dimensional space. We definite k-mean covering, and study its property. Covering subsets of points are repeatedly sampled to construct trial geometry space of various dimensions. The sampling corresponding to the feature space having the best cognition ability between a mode near zero and the rest is selected and the data points are partitioned on the basis of the best cognition ability. The repeated sampling then continues recursively on each block of the data. We propose this algorithm based on cognition models. The experimental results for face recognition demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high and effective.

Cancer subtypes recognition and its gene expression profiles analysis based on geometrical learning

The accurate recognition of cancer subtypes is very significant in clinic. Especially, the DNA microarray gene expression technology is applied to diagnosing and recognizing cancer types. This paper proposed a method of that recognized cancer subtypes based on geometrical learning. Firstly, the cancer genes expression profiles data was pretreated and selected feature genes by conventional method; then the expression data of feature genes in the training samples was construed each convex hull in the high-dimensional space using training algorithm of geometrical learning, while the independent test set was tested by the recognition algorithm of geometrical learning. The method was applied to the human acute leukemia gene expression data. The accuracy rate reached to 100%. The experiments have proved its efficiency and feasibility.