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2012 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2012

作者： Shen, Jing Sha, Wei E. I. Huang, Zhixiang Chen, Mingsheng Wu, Xianliang Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China Department of Electrical and Electronic Engineering University of Hong Kong Pokfulam Road Hong Kong Hong Kong Department of Physics and Electronic Engineering Hefei Normal University Lianhua Road Hefei 230601 China

ISBN: (纸本)9781467321839

A high-order symplectic FDTD (SFDTD) framework for solving the time-dependent Schrödinger equation is established. The third-order symplectic integrators and fourth-order collocated differences are employed in the time and space domains, respectively. The stabilities and numerical dispersions of FDTD(2,2), higher-order FDTD(2,4), and SFDTD(3,4) schemes are analyzed. We found that the stability limit of the SFDTD(3,4) scheme can be larger than that of the traditional FDTD(2,2) method through careful optimization of symplectic integrators. Moreover, the SFDTD(3,4) scheme and the FDTD(2,4) approach show better numerical dispersions than the traditional FDTD(2,2) method. © 2012 IEEE.

关键词： Numerical methods

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A new compressed sensing-based matching pursuit algorithm for image reconstruction

A new compressed sensing-based matching pursuit algorithm fo...

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Congress on Image and signal processing, CISP

作者： Hong Fang Hairong Yang School of Science Shanghai Second Polytechnic University Shanghai China Key Laboratory of Intelligent Computing Signal Processing Anhui University Hefei China

Compressed Sensing (CS), a popular technique which seeks to capture a discrete signal with a small number of linear measurements, could be used to compress a signal during the process of sampling. As an iterative greedy reconstruction algorithm for practical CS, sparsity adaptive matching pursuit (SAMP) takes advantage of the capability of signal reconstruction without prior information of the sparsity in the process of resuming the original high-dimension-data from low-dimension measurement. This paper presents a backward and adaptive matching pursuit reconstruction algorithm with fixed step sizes to avoid the overestimation phenomena of SAMP by using a standard regularized approach. Firstly, a fixed and biggish step size is set to make sure the size of support set of the signal to be reconstructed increasing stably. The energy difference between adjacent reconstructed signals is then taken as the halting condition of iteration. A standard regularized approach is employed to post-dispose the final iteration results, which backward eliminates superfluous atoms to acquire exact reconstruction. Experimental results show that such an improvement of SAMP is feasible in technology and effective in acquiring quick and exact reconstruction with sufficient measurement.

关键词： Matching pursuit algorithms Image reconstruction Accuracy Reconstruction algorithms Compressed sensing Minimization Sensors

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Analytical optimization for collaborative double threshold energy detection in cognitive radio network

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Journal of Information and Computational Science 2012年第13期9卷 3875-3882页

作者： Zhu, Jun Bai, Yun Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Electronic Information Engineering Anhui University Hefei 230601 China

The conventional 'OR' fusion rule is frequently applied in two pre-determined limits energy detection networks but its overall performance of the false alarm and miss detection probability is generally. The new method to optimize the total error probability in three combination schemes is proposed and the presented approach focuses on combining the k-out-of-N decision fusion with data fusion. General expressions for these probabilities are derived and an analytical solution for the optimal value of k is found minimizing the overall error probability. It provides performance analysis and comparison due to the different parameters such as SNR, the threshold coefficient, for the Additive White Gaussian Noise (AWGN) channel. Numerical experiment results show there are superior performances of above fusion strategies as opposed to traditional hard rule, by selecting the right system parameters. 1548-7741/Copyright © 2012 Binary Information Press.

关键词： Data fusion

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Clustering based on fuzzy tolerance quotient spaces

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Journal of Computational Information Systems 2012年第24期8卷 10105-10112页

作者： Zhao, Shu Zhang, Ling Liu, Qianqian Zhang, Yanping School of Computer Science and Technology Anhui University Hefei 230039 China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China

The quotient space theory based on fuzzy tolerance relation is put forward to solve the problem of clustering in this paper. The similarity matrix does not always satisfy ultrametric inequality, theoretically and practically. We give the method to construct the hierarchical quotient space chain if the similarity matrix is only reflexive and symmetric. We consider not only the subset of data (cluster) but also the structure of the different granular clusters. The main contributions in this paper include four parts. (1) We introduce sufficient and necessary condition that normalized distance d(x;y) is an equicrural distance;(2) The relation between equicrural distance and ultrametric inequality is discussed;(3) We propose a method to get the proximate partition of a covering from a tolerance relation;(4) An example for using fuzzy tolerance quotient spaces to clustering is given. © 2011 by Binary Information Press.

关键词： Information systems

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Iterative Annotation Transformation with Predict-Self Reestimation for Chinese Word Segmentation 12

Iterative Annotation Transformation with Predict-Self Reesti...

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Conference on Empirical Methods in Natural Language processing

作者： Wenbin Jiang Fandong Meng Qun Liu Yajuan Lue Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences

ISBN: (纸本)9781622765034

In this paper we first describe the technology of automatic annotation transformation, which is based on the annotation adaptation algorithm (Jiang et al., 2009). It can automatically transform a human-annotated corpus from one annotation guideline to another. We then propose two optimization strategies, iterative training and predict-self reestimation, to further improve the accuracy of annotation guideline transformation. Experiments on Chinese word segmentation show that, the iterative training strategy together with predict-self reestimation brings significant improvement over the simple annotation transformation baseline, and leads to classifiers with significantly higher accuracy and several times faster processing than annotation adaptation does. On the Penn Chinese Treebank 5.0, it achieves an F-measure of 98.43%, significantly outperforms previous works although using a single classifier with only local features.

关键词： ANNOTATIONS Classifiers Iterative Word Chinese Chinese philosophy Chinese art AUTOMATIC

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Pulse waveform key point recognition by wavelet transform for central aortic blood pressure estimation

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Journal of Information and Computational Science 2012年第1期9卷 25-33页

作者： Zheng, Gang Huang, Qingjun Yan, Guodong Dai, Min Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China Laboratory of Bio Signal and Intelligent Processing Tianjin University of Technology Tianjin 300384 China

Non invasion estimating of Central Aortic blood Pressure (CAP) is still a hard problem. Through tenyears clinical research plan (CAFE, Conduit Artery Functional Endpoint) on CAP, CAP is a vital sign to evaluate human's vascular condition. It is more valuable than ordinary brachial artery blood pressure. Non invasion estimating of CAP is depended on the key point recognition of radial pulse, especially the peak of tidal wave (left ventricular stopping ejection point, point e). Since someone's point e is not obvious in his/her pulse waveform, orientation of this point has becoming a difficult problem to be tackled. Through deep study on the feature of pulse waveform, an modified wavelet transform is proposed. It is used to recognize point e of pulse waveform by relative displacement between the 4th and 5th scale of a symlet (it is a kind of discrete wavelet transform). After experiments on 16 patients and 20 healthy volunteers, the results support the proposed strategy in recognizing both obvious and unobvious point e of pulse waveform. The CAP can be estimated by the point e accurately, and the results can meet the requirement of clinical diagnosis. © 2012 Binary Information Press January 2012.

关键词： Clinical research

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The structure of the sparse basis function in compressive sensing for fast analysis of wide-angle monostatic scattering problems

The structure of the sparse basis function in compressive se...

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2012 International Conference on Microwave and Millimeter Wave Technology, ICMMT 2012

作者： Du, Hong-Mei Chen, Ming-Sheng Wu, Xian-Liang Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei 230029 China Department of Physics and Electronic Engineering Hefei Normal University Hefei 230601 China University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781467321839

In the theory of compressive sensing, the selection of the basis functions directly affects the sparse transformation, observation number and reconstruction accuracy. In this paper, we introduce the structure of three sparse basic functions, which are used to analyze the electromagnetic scattering problems over a wide incident angle by the method of moment and compressive sensing. According to the characteristics of the induced current of wide angle, the best basic function is selected. Compared with the DCT, the accuracy of the reconstruction for different shape object are improved and the observation number reduces about 50%. © 2012 IEEE.

关键词： Method of moments

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A heuristic particle swarm optimization with quasi-human strategy for weighted circles packing problem

A heuristic particle swarm optimization with quasi-human str...

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International Conference on Natural Computation (ICNC)

作者： Ziqiang Li Yanfang Xie Zuijun Tian Zhou Lichao School of Information and Engineering Xiangtan University China 411105 Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan 411105 China Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education Xiangtan China

The weighted circles layout problem belongs to the layout optimization problem with performance constraints. Due to its NP-hard property, it is difficult to solve in polynomial time. In this paper, a heuristic particle swarm optimization approach with quasi-human strategy (HQHPSA) is presented for this problem. Its layout scheme is constructed through the proposed heuristic method: that both circular radius and the norm of row vector of the matrix and sub-vector are taken as the probability factors of the roulette selection and the circles are located by arranging round existing circles in peripheral with counterclockwise. The complexity of the proposed heuristic method is only O(n) for one layout scheme. The better layout solution obtained through the proposed heuristic method is taken as the elite particle individual. The PSO with quasi-human strategy is used to optimize the elite particle into the optimal solution. The numerical experiments show that the performance of proposed algorithm is superior to the existing algorithms.

关键词： Layout Algorithm design and analysis Particle swarm optimization Optimization Computers Genetic algorithms Educational institutions

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TINAC: A fast and effective web video topic detection framework

TINAC: A fast and effective web video topic detection framew...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xiang Ao Fuzhen Zhuang Qing He Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

Most of the previous works for web video topic detection(e.g., graph-based co-clustering method) always encounter the problem of real-time topic detection, since they all suffer from the high computation complexity. Therefore, a fast topic detection is needed to meet users' or administrators' requirement in real-world scenarios. Along this line, we propose a fast and effective topic detection framework, in which video streams are first partitioned into buckets using a time-window function, and then an incremental hierarchical clustering algorithm is developed, finally a video-based fusion strategy is used to integrate information from multiple modalities. Furthermore, a series of novel similarity metrics are defined in the framework. The experimental results on three months' YouTube videos demonstrate the effectiveness and efficiency of the proposed method.

关键词： Clustering algorithms Measurement Partitioning algorithms Streaming media Vectors Visualization Complexity theory

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Nested granular local learning

Nested granular local learning

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IEEE International Conference on Granular computing (GRC)

作者： Hong Hu Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

Local learning approaches are especially easy for parallel processing, so they are very important for cloud computing. In 1997, Lotti A. Zadeh proposed the concept of Granular computing (GrC). Zadeh proposed that there are three basic concepts that underlie human cognition: granulation, organization and causation and a granule being a clump of points (objects) drawn together by indistinguishability, similarity, proximity or functionality. In this paper, we give out a novel local learning approach based on the concept of Granular computing named as "nested local learning NGLL". The experiment shows that the novel NGLL approach is better than the probabilistic latent semantic analysis (PLSA).

关键词： Probabilistic logic Pattern recognition

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