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Degradation of AlGaN/GaN High Electron Mobility Transistors with Different AlGaN Layer Thicknesses under Strong Electric Field

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Chinese Physics Letters 2010年第2期27卷 243-245页

作者：杨凌马晶晶朱诚郝跃马晓华 Key Laboratory of Wide Band Gap Semiconductor Material and Device Institute of Microelectronics Xidian University Xi'an 710071 Key Laboratory of Intelligent Perception and Image Understanding (Ministry of Education) Institute of Intelligent Information Processing Xidian University Xi'an 710071 National Key Laboratory of Science and Technology on Antennas and Microwaves Xidian University Xi'an 710071

The degradation of AlGaN/GaN high electron mobility transistors （HEMTs） has a close relationship with a model of traps in AlGaN barriers as a result of high electric field. We mainly discuss the impacts of strong electrical field on the AlGaN barrier thickness of AlGaN/GaN HEMTs. It is found that the device with a thin AlGaN barrier layer is more easily degraded. We study the degradation of four parameters, i.e. the gate series resistance RGate, channel resistance R channel, gate current IG,off at VGS=-5 and VDS=0.1 V, and drain current ID,max at VGS=2 and VDS=5 V. In addition, the degradation mechanisms of the device electrical parameters are also investigated in detail.

关键词： Chinese climate network complex systems small world community

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CLUSTERING VIA DIMENSIONAL REDUCTION METHOD FOR THE PROJECTION PURSUIT BASED ON THE ICSA

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Journal of Electronics(China) 2010年第4期27卷 474-479页

作者： Gou Shuiping Feng Jing Jiao Licheng Key Laboratory of Intelligent Perception and Image Understanding for the Ministry of Education Institute of Intelligent Information Processing Xidian University Xi＇an 710071 China

The performance of the classical clustering algorithm is not always satisfied with the high-dimensional datasets, which make clustering method limited in many application. To solve this problem, clustering method with Projection Pursuit dimension reduction based on Immune Clonal Selection Algorithm (ICSA-PP) is proposed in this paper. Projection pursuit strategy can maintain consistent Euclidean distances between points in the low-dimensional embeddings where the ICSA is used to search optimizing projection direction. The proposed algorithm can converge quickly with less iteration to reduce dimension of some high-dimensional datasets, and in which space, K-mean clustering algorithm is used to partition the reduced data. The experiment results on UCI data show that the presented method can search quicker to optimize projection direction than Genetic Algorithm (GA) and it has better clustering results compared with traditional linear dimension reduction method for Principle Component analysis (PCA).

关键词： Projection Pursuit (PP) Immune Clonal Selection Algorithm (ICSA) Genetic Algorithm (GA) K-means clustering

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A multiobjective immune clustering ensemble technique applied to unsupervised SAR image segmentation 10

A multiobjective immune clustering ensemble technique applie...

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ACM International Conference on image and Video Retrieval, ACM-CIVR 2010

作者： Liu, Ruochen Zhang, Wei Jiao, Licheng Liu, Fang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an China

ISBN: (纸本)9781450301176

In the past few years, multiobjective clustering has been one of the most successful techniques in the field of computer vision and data clustering. This paper proposes a novel unsupervised approach for synthetic aperture radar (SAR) image segmentation, namely, multiobjective immune clustering ensemble technique (MICET). The new technique first divides the image into several regions, and a certain number of pixels are picked out from these regions to form the clustering dataset. Second, artificial immune system (AIS) and multiobjective optimization (MOO) are introduced to generate multiple clustering results, which are then combined together for the following ensemble process. Multiple runs of the multiob-jective clustering method with different randomly selected image features are performed to ensure high quality components as well as necessary diversity for an efficient ensemble. Finally, each datum is assigned to one cluster according to the relationship with the clustering dataset. Experimental results show that interesting segmentation performances on SAR images can be achieved by the proposed technique despite its completely unsupervised nature. Copyright © 2010 ACM.

关键词： Multiobjective optimization

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Algorithm of partition based network boosting for imbalanced data classification

Algorithm of partition based network boosting for imbalanced...

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2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010

作者： Shuiping, Gou Hui, Yang Licheng, Jiao Xiong, Zhuang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424469178

Network Boosting (NB) is an ensemble learning method which combines weak learners together based on a network and can learn the target hypothesis asymptotically. NB has higher generalization ability compared to Bagging and AdaBoost. But, when datasets are class-imbalanced, the performance of NB will decrease quickly. In order to solve this problem, we present a Partition based Network Boosting method (PNB) to classify imbalanced data. For PNB method, every classifier node of the classifier network is provided with the same number of training data which are all of same weights. The classifier in the network is built by the balanced training set sampled from the training data according to the weights record of the training data it holds. And then, the weights of the instances of every node classifier are updated based on the classification results of self-node and its neighbor nodes. The classifier network is trained repeatedly in such a way. Weight factor of hypothesis in the training progress is introduced to improve the performance. The final classification is formed by all the hypotheses of the classifier network learned during the training progress so that the label of new instances can be decided by the weight voting. The experimental results on UCI data and imbalanced biomedical data show that the PNB algorithm has better AUC and recall performance compared with NB learning machine. © 2010 IEEE.

关键词： Adaptive boosting

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Observer-based adaptive tracking control of rigid-link flexible-joint robot manipulators

Observer-based adaptive tracking control of rigid-link flexi...

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作者： Liu, Chao Xiang, Xianbo Poignet, Philippe France Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China

ISBN: (纸本)9787894631046

Joint flexibility is an important factor to consider in the robot control design if high performance is expected for the robot manipulators. Research works on control of rigid-link flexible-joint (RLFJ) robot in literature have assumed that the kinematics of the robot is known exactly. There have been few results that can deal with the kinematics uncertainty in RLFJ robot. In this paper, we propose an adaptive tracking control method which can deal with the kinematics uncertainty and uncertainties in both link and actuator dynamics of the RLFJ robot system. Nonlinear observers are designed to avoid accelerations measurement due to the fourth-order overall system dynamics. Asymptotic stability of the closed-loop system is shown and sufficient conditions are presented to guarantee the stability.

关键词： Asymptotic stability

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One-time-pads encryption in the tile assembly model

One-time-pads encryption in the tile assembly model

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作者： Chen, Zhihua Xu, Jin Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

Recent research has demonstrated that the ultra-scale computation by self-assembly DNA tiles can be implemented in the laboratory. One of the significant applications is the DNA-based cryptography systems. In this paper, we detail procedures for the DNA-based One-Time-Pads (OTP) cryptography, which is in principle unbreakable. In order to implement the whole encrypting and decrypting processes, we propose four tile systems: encrypting system, ciphertext extracting system, key extracting system and decrypting system. All the tile systems use θ(1) input tiles and compute in θ(n) steps according to the length of the input massage. The method of implementing the DNA OTP encryption extends the self-assemble tile models and achieves the real randomness in the DNA OTP. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Cryptography

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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2010 International Conference on intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation analysis (CCA) and the spatial Independent Component analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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Small universal spiking neural p systems with exhaustive use of rules

Small universal spiking neural p systems with exhaustive use...

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作者： Zhang, Xingyi Jiang, Yun Pan, Linqiang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

We consider the problem of looking for small universal spiking neural P systems with exhaustive use of rules, which was formulated as an open problem by Andrei PǍun and Gheorghe PǍun in a survey paper. Here, spiking neural P systems are used in two versions: as devices computing functions and as devices generating sets of numbers, with two ways of encoding the result of a computation. As devices of computing functions, if we associate the result with the distance between the first two spikes emitted by the output neuron, we produce a universal computing spiking neural P system with exhaustive use of rules (without delay) having 125 neurons;if we introduce the usual way of defining the result of a computation in membrane systems to encode the result, namely, the number of spikes emitted during a computation, then a universal computing system (without delay) with 126 neurons is also obtained in the sense of the exhaustive use of rules. For spiking neural P systems used as generators of sets of numbers, we construct a universal system (without delay) by using 128 neurons under the first way of defining the computation result, and a system (without delay)by using127 neurous under the second way of defining the comutation result. Copyright © 2010 American Scientific Publishers. All rights reserved.

关键词： Neurons

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A note on small universal spiking neural P systems

A note on small universal spiking neural P systems

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10th International Workshop on Membrane Computing, WMC 2009

作者： Pan, Linqiang Zeng, Xiangxiang Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)3642114660

In the "standard" way of simulating register machines by spiking neural P systems (in short, SN P systems), one neuron is associated with each instruction of the register machine that we want to simulate. In this note, a new way is introduced for simulating register machines by SN P systems, where only one neuron is used for all instructions of a register machine;in this way, we can use less neurons to construct universal SN P systems. Specifically, a universal system with extended rules (without delay) having 10 neurons is constructed. © 2010 Springer-Verlag.

关键词： Neurons

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Small universal asynchronous spiking neural P systems

Small universal asynchronous spiking neural P systems

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Pan, Linqiang Zeng, Xiangxiang Zhang, Xinyi Department of Control Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 Hubei China

ISBN: (纸本)9781424464388

Looking for small universal computing devices is a natural and well investigated topic in computer science. Recently, this topic started to be considered also in the framework of (synchronized) spiking neural P systems. In this work, it is focused on small universal spiking neural P systems working in a non-synchronized manner. Specifically, it is proved that there is an asynchronous spiking neural P system with 76 neurons that is equivalent to a universal register machine for computing functions. As generator of sets of numbers, a universal asynchronous spiking neural P system with 75 neurons is constructed. © 2010 IEEE.

关键词： biocomputing computer science neural chips small universal computing devices universal asynchronous spiking neural P system universal register machine

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