Effects of 9-cyanoanthracene and anthracene adsorption on the photoluminescence of porous silicon

The photoluminescence of porous silicon can be modified sensitively by surface adsorption of different kinds of molecules. A quite different effects of 9-cyanoanthracene and anthracene adsorption on the photoluminescence of porous silicon were observed. The adsorption of 9-cyanoanthracene induced the photoluminescence enhancement, while anthracene adsorption resulted in photoluminescent quenching. An explanation of the interaction of adsorbates with surface defect sites of porous silicon was suggested and discussed. (C) 1998 Elsevier Science S.A.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Theoretical analysis of modal gain in p-doped 1.3 mu m InAs/GaAs quantum dot lasers

A theoretical study of modal gain in p-doped 1.3 mu m InAs/GaAs quantum dot (QD) lasers is presented. The expression of modal gain is derived, which includes an effective ratio that describes how many QDs contribute to the modal gain. The calculated results indicate that the modal gain with the effective ratio is much smaller than that without the effective ratio. The calculated maximum modal gain is is a good agreement with the experimental data. Furthermore, QDs with lower height or smaller aspect ratio are beneficial in achieving a larger maximum modal gain that leads to lower threshold current density and higher differential modal gain. (C) 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

A Compact Direct Digital Frequency Synthesizer for System-on-chip

A compact direct digital frequency synthesizer (DDFS) for system-on-chip (SoC) is developed in this paper. For smaller chip size and lower power consumption, the phase to sine mapping data is compressed by using sine symmetry technique, sine-phase difference technique, quad line approximation (QLA) technique and quantization and error read only memory (QE-ROM) technique. The ROM size is reduced by 98 % using the techniques mentioned above. A compact DDFS chip with 32-bit phase storage depth and a 10-bit on-chip digital to analog converter(DAC) has been successfully implemented using standard 0.35um CMOS process. The core area of the DDFS is 1.6mm(2). It consumes 167 mW at 3.3V, and its spurious free dynamic range (SFDR) is 61dB.

Leakage current analysis in AlGaInP/GaInP multi-quantum well lasers by the electrical derivative method - art. no. 60202F

In AlGaInP/GaInP multi-quantum well (MQW) lasers, the electron leakage current is a much more serious problem than that in laser diodes with longer wavelength. To further improve the output performance, the leakage current should be analyzed. In this letter, the temperature dependence of electrical derivative characteristics in AlGaInP/GaInP multi-quantum well lasers was measured, and the potential barrier for electron leakage was obtained. With the help of secondary ion mass spectroscopy (SIMS) measurement, theoretical analysis of the potential barrier was presented and compared with the measurement result. The influence of p-cladding doping level and doping profile on the potential barrier was discussed, and this can be helpful in metalorganic chemical vapor deposition (MOCVD) growth.

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.

Face recognition based on PCA and multi-degree of freedom neurons

An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.

Study on text-dependent speaker recognition based on Biomimetic Pattern Recognition

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.

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.

Continuous speech recognition based on ICA and geometrical learning

We investigate the use of independent component analysis (ICA) for speech feature extraction in digits speech recognition systems. We observe that this may be true for recognition tasks based on Geometrical Learning with little training data. In contrast to image processing, phase information is not essential for digits speech recognition. We therefore propose a new scheme that shows how the phase sensitivity can be removed by using an analytical description of the ICA-adapted basis functions. Furthermore, since the basis functions are not shift invariant, we extend the method to include a frequency-based ICA stage that removes redundant time shift information. The digits speech recognition results show promising accuracy. Experiments show that the method based on ICA and Geometrical Learning outperforms HMM in a different number of training samples.

Research on multi-degree-of-freedom neurons with weighted graphs

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.

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.

Continuous speech research based on HyperSausage Neuron

In this paper, we presents HyperSausage Neuron based on the High-Dimension Space(HDS), and proposes a new algorithm for speaker independent continuous digit speech recognition. At last, compared to HMM-based method, the recognition rate of HyperSausage Neuron method is higher than that of in HMM-based method.

The effect of Fabry-Perot interference on the packaging of SOI-based optoelectronic devices

During the packaging of optoelectrome device, a problem always met is the instability of output power. The main effect causing this problem, Fabry-Perot interference, is discussed in this paper. Both theoretical analysis and experimental test are carried out and in good agreement. As an example of avoiding the disadvantage of Fabry-Perot interference, the packaging process of Silicon-on-Insulator (SOI) based Variable Optical Attenuator(VOA) is shown at last.

Theoretical analysis of the bandgap for the intermixed GaInP/AlGaInP quantum wells

Compositional distribution of the quantum well and barrier after quantum well intermixing for GaInP/AlGaInP system was theoretically analyzed on the basis of atom diffusion law. With the compositional distribution result, the valence subband structure of the intermixed quantum well was calculated on the basis of 6x6 Luttinger-Kohn Hamiltonian, including spin-orbit splitting effects. TO get more accurate results in the calculation, a full 6-band problem was solved without axial approximation, which had been widely used in the Luttinger-Kohn model to simplify the computational efforts, since there was a strong warping in the GaInP valence band. At last, the bandgap energy of the intermixed quantum well was obtained and the calculation result is of much importance in the analysis of quantum well intermixing experiments.