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IEEE International Symposium on Biomedical Imaging

作者： K. S. Kim Y. D. Son Z. H. Cho J. B. Ra J. C. Ye Bio Imaging & Signal Processing Laboratory Department of Bio& Brain Engineering Korea Advanced Institute of Science and Technology South Korea Neuroscience Research Institute Gachon University of Medicine and Science South Korea Image Systems Laboratory Electrical Engineering Korea Advanced Institute of Science and Technology South Korea

ISBN: (纸本)9781467364560

Dynamic positron emission tomography (PET) is widely used to measure variations of radiopharmaceuticals within the organs over time. However, conventional reconstruction algorithm can produce a noisy reconstruction if there are not sufficient photon counts. Hence, the main goal of this paper is to develop a novel spatio-temporal regularization approach that exploits inherent similarities within intra- and inter-frames to overcome the limitation. One of the main contributions of this paper is to demonstrate that such correlations can be exploited using a low rank constraint of overlapping similarity blocks. The resulting optimization framework is, however, non-smooth and non Lipschitz due to the low-rank penalty terms and Poisson log-likelihood. Therefore, we propose a novel globally convergent optimization method using the concave-convex procedure (CCCP) by exploiting Legendre-Fenchel transform, which overcomes the memory and computational limitations. We confirm that the proposed algorithm can provide significantly improved image quality and extract accurate kinetic parameters.

关键词： Image reconstruction Positron emission tomography Heuristic algorithms Graphics processing units Minimization Optimization Biomedical imaging

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A Study of the Three-Term Non-Gaussian Pre-Stack Inversion Method

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Chinese Journal of Geophysics 2013年第1期55卷 55-64页

作者： Yang LIU Jia-Shu ZHANG Guang-Min HU Zhen-Hua HE Sichuan Key Lab of Signal and Information Processing Southwest Jiaotong University Chengdu 610031 China Key Laboratory of Broadband Optical Fiber Transmission and Communication Networks University of Electronic Science and Technology of China Chengdu 611731 China State Key Laboratory of Oil and Gas Reservoir Geology and Exploration Chengdu University of Technology Chengdu 610059 China

In view of the wide use of the “Gaussian distribution hypothesis of noise” in geophysical inversion problems, we study the non-Gaussian distribution characteristics of the noise in pre-stack seismic data. Upon this analysis, the concept of non-Gaussian inversion of pre-stack three-term inversion is put forward, in which the mixed-norm is proposed for suppressing both the Gaussian and non-Gaussian noises. In view of the non-derivable feature of the objective function, the Powell algorithm is used to solve the objective function. Model test and real seismic data inversion results show the correctness and reliability of the algorithm.

关键词： Prestack inversion Non-Gaussian Mixed norm Powell algorithm

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Relationship exploration among PPI, ATGP and VCA via theoretical analysis

Relationship exploration among PPI, ATGP and VCA via theoret...

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作者： Chang, Chein-I. Wen, Chia-Hsien Wu, Chao-Cheng Department of Computer Science and Electrical Engineering Remote Sensing Signal and Image Processing Laboratory University of Maryland 1000 Hilltop Circle Baltimore MD 21250 United States Department of Computer Science and Information Engineering Providence University Taichung Taiwan Department of Computer Science and Information Management Providence University 200 Taiwan Boulevard Shalu Dist. Taichung City 43301 Taiwan Department of Electrical Engineering National Taipei University of Technology 1 Zhongxiao E. Rd. Taipei 106 Taiwan

The principle of orthogonality using orthogonal projection (OP) is the key concept to develop mean squared error estimation theory in signal processing and communications. It has also found its way in a wide variety of applications in hyperspectral imaging. This paper explores close relationships among three OP-based algorithms, pixel purity index (PPI), vertex component analysis (VCA) in endmember extraction, automatic target generation process (ATGP) in mixed pixel classification and target detection, etc. and further shows that they indeed can be interpreted one way or another. Specifically, VCA and ATGP are essentially the same algorithm in the sense that they both extract targets via maximal OP from a nested sequence of successive orthogonal subspace projection spaces. Copyright © 2013 Inderscience Enterprises Ltd. Copyright © 2013 Inderscience Enterprises Ltd.

关键词： Hyperspectral imaging

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The observability analysis of aerial moving target location based on dual-satellite geolocation system

The observability analysis of aerial moving target location ...

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2012 International Conference on Computer science and Information processing, CSIP 2012

作者： Deng, Bing Xiong, Jinyu Xia, Changxiong Science and Technology on Blind Signal Processing Laboratory Chengdu China

ISBN: (纸本)9781467314114

Dual-satellite geolocation system is an effective passive location technique. This method can locate a stationary emitter on Earth by using time and frequency differences of arrival (TDOA/FDOA).In this paper, the rank of the observation matrix was proposed as standards of location observability, established location models, analysed the observability of aerial moving target location with the representative motion, such as uniform linear model and maneuvering turn model. Finally, simulation results presented a conclusion that Dual-satellite geolocation system could implement location for aerial moving target under some restrictions. In this paper, the rank of the observation matrix was proposed as standards of location observability, established location models, analysed the observability of aerial moving target location with the representative motion, such as uniform linear model and maneuvering turn model. Finally, simulation results presented a conclusion that Dual-satellite geolocation system could implement location for aerial moving target under some restrictions. © 2012 IEEE.

关键词： Observability

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A uniform solution to the independent set problem through tissue P systems with cell separation

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Frontiers of Computer science 2012年第4期6卷 477-488页

作者： Xingyi ZHANG Xiangxiang ZENG Bin LUO Zheng ZHANG Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230039China Department of Computer Science Xiamen UniversityXiamen 361005China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074China

Membrane computing is an emergent branch of natural computing, which is inspired by the structure and the functioning of living cells, as well as the organization of cells in tissues, organs, and other higher order structures. Tissue P systems are a class of the most investigated computing mod- els in the framework of membrane computing, especially in the aspect of efficiency. To generate an exponential resource in a polynomial time, cell separation is incorporated into such systems, thus obtaining so called tissue P systems with cell separation. In this work, we exploit the computational efficiency of this model and construct a uniform family of such tissue P systems for solving the independent set problem, a well-known NP-complete problem, by which an efficient so- lution can be obtained in polynomial time.

关键词： membrane computing tissue P system cell sep- aration independent set problem

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Weighted constrained total least-square algorithm for source localization using TDOA measurements

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2011 International Conference on Future Wireless Networks and Information Systems, ICFWI 2011

作者： Jing-Min, Cao He-Wen, Wei Jian, Yu Science and Technology on Blind Signal Processing Laboratory Chengdu 610041 China

ISBN: (纸本)9783642273223

A weight constrained total least-square (WCTLS) is developed for source localization by using time difference of arrival (TDOA) measurements. The WCTLS algorithm not only exploits the structure information of the measurement matrix, but also utilizes the prior knowledge of the TDOA measurements. The bias and covariance of the proposed WCTLS algorithm are also analyzed. Simulation results show that the proposed estimator achieves better performance than that of the constrained total least square, and it attains the Cramer-Rao lower bound at a sufficiently low noise level. © 2012 Springer-Verlag GmbH.

关键词： Time difference of arrival

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Multi-objects classification via optimized compressive sensing projection

Multi-objects classification via optimized compressive sensi...

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International Conference on Information, Communications and signal processing

作者： A. H. Yu H. Bai Q. R. Jiang Z. H. Zhu C. G. Huang G. Li B. P. Hou Zhejiang Provincial Key Laboratory for Signal Processing College of Information Engineering Zhejiang University of Technology Hangzhou Zhejiang P.R. China School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou Zhejiang P.R. China

The theory of compressive sensing (CS) enables the reconstruction of a sparse signal from highly compressed data. However, in many applications, we are ultimately interested in information retrieval rather than signal reconstruction. In this paper, we study the problem of multi-objects classification in compressive sensing systems. Theoretical error bounds are derived based on the analysis of classical compressive classification. The optimal projection matrix design problem is studied and an algorithm is derived to solve the corresponding problem. Application in the identification of license plate numbers is considered and simulation results show that the projection measurement obtained using the proposed algorithm significantly improve the classification performance in terms of classification error rate.

关键词： Licenses Sensors Dictionaries Coherence Compressed sensing Image coding signal processing

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Dynamics of a Cortical Neural Network Based on a Simple Model

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Chinese Physics Letters 2012年第8期29卷 52-55页

作者： QU Jing-Yi WANG Ru-Bin Tianjin Key Laboratory for Advanced Signal Processing Civil Aviation UniversityTianjin 300300 Institute for Cognitive Neurodynamics School of ScienceEast China University of Science and TechnologyShanghai 200237

The collective dynamics of a randomly connected neuronal network motivated by the anatomy of a mammalian cortex based on a simple model are *** simple model can not only reproduce the rich behaviors of biological neurons but also has only two equations and one nonlinear *** varying some key parameters,such as the connection weights of neurons,the external current injection and the noise of intensity,this neuronal network will exhibit various collective *** is demonstrated that the synchronization status of the neuronal network has a strong relationship with the key parameters and the external current has more influence on the spiking of inhibitory neurons than that of excitatory *** results may be instructive in understanding the collective dynamics of a mammalian cortex.

关键词： anatomy collective cortex

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Airborne GMTI experiment based on multi-channel synthetic aperture radar using space time adaptive processing

Airborne GMTI experiment based on multi-channel synthetic ap...

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作者： Yang, Zhiwei Liao, Guisheng He, Shun Zeng, Cao National Laboratory of Radar Signal Processing Xidian University 710071 China Communication and Information Engineering College Xian University of Science and Technology 710054 China

The non-ideal conditions of real-world detection environments, such as beam-pattern mismatch, non-ideal sensor geometry, receiver channel imbalance and clutter heterogeneity, can preclude the performance described in much of the theoretical STAP literature. For the purpose of overcoming those problems, a new target detection and location approach with low complexity is proposed. This presented algorithm is performed in three stages, i.e. array manifold adaptive calibration, clutter rejection in Winner filter sense and target parameters estimation using modified single-snapshot multiple direction of arrival estimation method. The array manifold calibration procedure uses a power-based criterion to reject a weak clutter patch and/or target for covariance matrix estimation, meanwhile, a phase-based criterion is adopted to alleviate the strong target signal contamination problem. Once the array has been calibrated, adaptive clutter and/or jamming cancellation can be achieved in the Wiener filter sense. This step does not require angle-Doppler bin searching. The last stage is carried out at the determinate range-Doppler test cell to locate moving target by azimuth searching for that one fitting best to the moving target signal, thus the location performance would not be sacrificed in order to suppress clutter and/or interference and the high resolution radial velocity estimation can be achieved. Therefore, the proposed algorithm is computationally inexpensive and is better suited to work in real-world detection environments. A preliminary result against an airborne experimental data demonstrates the effectiveness of the proposed method. © 2011 Elsevier Masson SAS. All rights reserved.

关键词： Space time adaptive processing

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A DSmT Based Combination Scheme for Multi-Class Classification

A DSmT Based Combination Scheme for Multi-Class Classificati...

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International Conference on Information Fusion

作者： Nassim Abbas Youcef Chibani Zineb Belhadi Mehdia Hedir Speech Communication and Signal Processing Laboratory Faculty of Electronics and Computer Science University of Science and Technology Houari Boumediene (USTHB)

ISBN: (纸本)9781479902842

This paper presents a new combination scheme for reducing the number of focal elements to manipulate in order to reduce the complexity of the combination process in the multiclass framework. The basic idea consists in using of p sources of information involved in the global scheme providing p kinds of complementary information to feed each set of p one class support vector machine classifiers independently of each other, which are designed for detecting the outliers of the same target class, then, the outputs issued from this set of classifiers are combined through the plausible and paradoxical reasoning theory for each target class. The main objective of this approach is to render calibrated outputs even when less complementary responses are encountered. An inspired version of Appriou's model for estimating the generalized basic belief assignments is presented in this paper. The proposed methodology allows decomposing a n-class problem into a series of n-combination, while providing n-calibrated outputs into the multi-class framework. The effectiveness of the proposed combination scheme with proportional conflict redistribution algorithm is validated on digit recognition application and is compared with existing statistical, learning, and evidence theory based combination algorithms.

关键词： Conflict management Dezert-Smarandache theory Handwriting digit recognition Support Vector Machines

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