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IEEE Long Island Systems, Applications and Technology Conference (LISAT)

作者： Muder M. Almi'ani Buket D. Barkana Department of Computer Information Systems Al-Hussein Bin Talal University Signal Processing Research Group Laboratory University of Bridgeport Bridgeport CT USA Department of Electrical Engineering Signal Processing Research Group Laboratory University of Bridgeport Bridgeport CT USA

The progress of medical imaging instrumentation has stirred the development of new computer-aided methods of image processing and analysis for better understanding and interpretation of medical images for differential diagnosis, intervention, and treatment monitoring. Image processing and analysis methods have been used to help physicians to make important medical decisions through physician-computer interaction. A modified region growing algorithm is proposed to extract cerebral vessels using a magnetic resonance angiography (MRA) database. To improve the performance of the image segmentation method, as a pre-processing step, image enhancement methods are applied by the gamma correction technique and spatial operations. This step improves the detection of gray-level discontinuities in MRA images. The traditional region growing method is modified by extending the neighborhood as 24 pixels and by defining a filling protocol to label vascular structure. The performance of the proposed algorithm is compared with that of the traditional region growing method and four other segmentation methods. Our proposed method outperformed the other methods. The minimum and maximum errors of the modified region growing method is calculated as zero and 0.82, respectively while the traditional region growing method has 1.85 and 21.91.

关键词： Image segmentation Blood vessels Angiography Filling Magnetic resonance Protocols

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IRCI free range reconstruction for co-located MIMO-OFDM radar

IRCI free range reconstruction for co-located MIMO-OFDM rada...

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IEEE China Summit & International Conference on Signal and Information processing (ChinaSIP)

作者： Yunhe Cao Xiang-Gen Xia Shenghua Wang National Laboratory of Radar Signal Processing Xidian University Xi'an P.R. China Department of Electrical and Computer Engineering University of Delaware Newark DE USA

ISBN: (纸本)9781479919499

A MIMO-OFDM range reconstruction method based on cyclic prefix (CP) and its corresponding MIMO-OFDM waveform design for co-located MIMO radar systems are proposed. Our proposed MIMO-OFDM waveform design achieves the maximum signal-to-noise ratio (SNR) gain after the range reconstruction and its peak-to-average power ratio (PAPR) in the discrete time domain is also optimal, i.e., 0dB, when Zadoff-Chu sequences are used in the discrete frequency domain as the weighting coefficients for the subcarriers. Finally, simulation results are presented to verify the effectiveness of the proposed method.

关键词： OFDM Receiving antennas MIMO radar Transmitting antennas Radar antennas Scattering

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A novel hybrid optimization algorithm and its application in solving complex problem

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International Journal of Hybrid Information Technology 2015年第2期8卷 1-10页

作者： Jia, Hao Department of Electrical Engineering Dalian Institute of Science and Technology Dalian116052 China The Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China

Ant colony optimization (ACO) algorithm is a new heuristic algorithm which has been demonstrated a successful technology and applied to solving complex optimization problems. But the ACO exists the low solving precision and premature convergence problem, particle swarm optimization (PSO) algorithm is introduced to improve performance of the ACO algorithm. A novel hybrid optimization (HPSACO) algorithm based on combining collaborative strategy, particle swarm optimization and ant colony optimization is proposed for the traveling salesman problems in this paper. The HPSACO algorithm makes use of the exploration capability of the PSO algorithm and stochastic capability of the ACO algorithm. The main idea of the HPSACO algorithm uses the rapidity of the PSO algorithm to obtain a series of initializing optimal solutions for dynamically adjusting the initial pheromone distribution of the ACO algorithm. Then the parallel search ability of the he ACO algorithm are used to obtain the optimal solution of solving problem. Finally, various scale TSP are selected to verify the effectiveness and efficiency of the proposed HPSACO algorithm. The simulation results show that the proposed HPSACO algorithm takes on the better search precision, the faster convergence speed and avoids the stagnation phenomena. © 2015 SERSC.

关键词： Traveling salesman problem

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AN OVERVIEW OF ROBUST COMPRESSIVE SENSING OF SPARSE SIGNALS IN IMPULSIVE NOISE

AN OVERVIEW OF ROBUST COMPRESSIVE SENSING OF SPARSE SIGNALS ...

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European Signal processing Conference

作者： Ana B. Ramirez Rafael E. Carrillo Gonzalo Arce Kenneth E. Barner Brian Sadler Universidad Industrial de Santander Signal Processing Laboratory (LTS5) Ecole Polytechnique Federale de Lausanne (EPFL) Department of Electrical and Computer Engineering University of Delaware US Army Research Laboratory

ISBN: (纸本)9781479988518

While compressive sensing (CS) has traditionally relied on l_2 as an error norm, a broad spectrum of applications has emerged where robust estimators are required. Among those, applications where the sampling process is performed in the presence of impulsive noise, or where the sampling of the high-dimensional sparse signals requires the preservation of a distance different than l_2. This article overviews robust sampling and nonlinear reconstruction strategies for sparse signals based on the Cauchy distribution and the Lorentzian norm for the data fidelity. The derived methods outperform existing compressed sensing techniques in impulsive environments, thus offering a robust framework for CS.

关键词： Compressed sensing Sampling methods Robust signal reconstruction Nonlinear estimation Impulsive noise Impulse noise Compressed sensing nonlinear estimation sampling methods signals Spectra applications sampling process Noise

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Gaussian Mixture Model Based Interest Prediction In Social Networks

Gaussian Mixture Model Based Interest Prediction In Social N...

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Dongyun An Xianghan Zheng Chunming Rong Tahar Kechadi ChongCheng Chen College of Mathematics and Computer Science Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Department of Electrical Engineering and Computer Science Stavanger Norway University College Dublin School of Computer Science and Informatics Ireland

In this paper, we investigate a typical clustering technology, namely, Gaussian mixture model (GMM)-based approach, for user interest prediction in social networks. The establishment of the model follows the following process: collect dataset from 4613 users and more than 16 million messages from Sina Weibo, obtain each user's interest eigenvalue sequence and establish GMM model to clustering users. In theory and experiment, this approach is feasible. The GMM-based approach considers the prediction accuracy and consuming time. A series of experiments are conducted to validate the feasibility and efficiency of the proposed solution and whether it can achieve a higher accuracy of prediction compared with other approaches, such as SVM and K-means. Further experiments show that GMM-based approach could produce higher prediction accuracy of 93.9%, thus leveraging computation complexity.

关键词： Predictive models Feature extraction Social network services Gaussian mixture model Eigenvalues and eigenfunctions Clustering algorithms

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Improving vertex-frontier based GPU breadth-first search

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Journal of Central South University 2014年第10期21卷 3828-3836页

作者：杨博卢凯高颖慧徐凯王小平程志权 Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology College of Computer National University of Defense Technology Department of Electronic Science and Engineering National University of Defense Technology Avatar Science Company

Breadth-first search(BFS) is an important kernel for graph traversal and has been used by many graph processing applications. Extensive studies have been devoted in boosting the performance of BFS. As the most effective solution, GPU-acceleration achieves the state-of-the-art result of 3.3×109 traversed edges per second on a NVIDIA Tesla C2050 GPU. A novel vertex frontier based GPU BFS algorithm is proposed, and its main features are three-fold. Firstly, to obtain a better workload balance for irregular graphs, a virtual-queue task decomposition and mapping strategy is introduced for vertex frontier expanding. Secondly, a global deduplicate detection scheme is proposed to remove reduplicative vertices from vertex frontier effectively. Finally, a GPU-based bottom-up BFS approach is employed to process large frontier. The experimental results demonstrate that the algorithm can achieve 10% improvement over the state-of-the-art method on diverse graphs. Especially, it exhibits 2-3 times speedup on low-diameter and scale-free graphs over the state-of-the-art on a NVIDIA Tesla K20 c GPU, reaching a peak traversal rate of 11.2×109 edges/s.

关键词： breadth-first search GPU graph traversal vertex frontier

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Risk Management Using Big Real Time Data

Risk Management Using Big Real Time Data

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Jie Cheng Chunming Rong Huijuan Ye Xianghan Zheng Department of Electrical Engineering and Computer Science Risk Management Using Big Real Time Data Department of Computer Science and Electronic Engineering University of Stavanger Stavanger Norway College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China

Adding to societal changes today, are the miscellaneous big data produced in different fields. Coupled with these data is the appearance of risk management. Admittedly, to predict future trend by using these data is conducive to make everything more efficient and easy. Now, no matter companies or individuals, they increasingly focus on identifying risks and managing them before risks. Effective risk management will lead them to deal with potential problems. This thesis focuses on risk management of flight delay area using big real time data. It proposes two different prediction models, one is called General Long Term Departure Prediction Model and the other is named as Improved Real Time Arrival Prediction Model. By studying the main factors lead to flight delay, this thesis takes weather, carrier, National Aviation System, security and previous late aircraft as analysis factors. By utilizing our models can do not only long time but also short term flight delay predictions. The results demonstrate goodness of fit. Besides the theory part, it also presents a practical and beautiful web application for real time flight arrival prediction based on our second model.

关键词： Delays Biological system modeling Meteorology Atmospheric modeling Predictive models Airports Splines (mathematics)

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Design of a configurable fixed-point FFT processor

Design of a configurable fixed-point FFT processor

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IET International Radar Conference 2015

作者： Chen Yang Yi-zhuang Xie Liang Chen He Chen Yi Deng Beijing Key laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing China Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA USA

ISBN: (纸本)9781510822023

In this paper, we focus on the widely-used radix-2 2 Decimation-In-Frequency (DIF) Fast Fourier Transform (FFT) algorithm. A variable-length, controllable-precision FFT processor is proposed. The processor can perform 16, 64, 256 and 1024 point FFT/IFFT and provide flexible wordlength scaling modes for different FFT stages. Thus, the processor is suitable for different precision and FFT length requirements in various applications. Aiming at high throughput performance, single-path delay feedback (SDF) pipeline architecture is adopted. The design is testified on Xilinx Virtex6 xc6vcx240t FPGA. Accordingly, we make a clear comparison between the proposed design and Xilinx FFT v7.1. Our design achieves better signal-to-quantizationnoise ratio (SQNR) property and shorter pipeline latency. Meanwhile, the occupied resource is approximately the same. Moreover, SQNR performance of different FFT length and wordlength scaling modes is analysed.

关键词： FFT Configurable Fixed-point FPGA

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Fixed-point simulation technology for SAR real-time imaging system

Fixed-point simulation technology for SAR real-time imaging ...

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IET International Radar Conference 2015

作者： Xin Zhou Yi-zhuang Xie Chen Yang Qing Du Yi Deng Beijing Key Laboratory of Embedded Real-time Information Processing Technology Beijing Institute of Technology Beijing 100081 China Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington VA USA

ISBN: (纸本)9781510822023

In this paper, a fast fixed-point simulation technology is proposed for a multi-channel synthetic aperture radar (SAR) imaging system. The overall computations in the SAR imaging algorithm is explicitly analysed. FFT operations account for most memory consumption in the imaging flow. Accordingly, a fixed-point FFT algorithm is adopted due to the trade-off between precision and memory occupation of the FPGA implementation. Furthermore, this paper describes an optimized word-length configuration method based on theoretical analysis of architecture of Radix-22 FFT. This methodology is verified in a SystemC development environment due to its superiority of fast and bit-accurate system-level simulation capability. Finally, the proposed SystemC based fixed-point imaging algorithm and the Matlab based floating-point imaging algorithm are both conducted to process point array target raw data. Peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR) is evaluated. Experimental results indicate that profiles in the two cases do not differ greatly, which validates that the proposed fixedpoint algorithm with less resources occupation has comparable accuracy and can meet system requirements.

关键词： SAR SystemC fixed-point arithmetic real-time imaging system-level simulation

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Markov Chain Monte Carlo inference on graphical models using event-based processing on the SpiNNaker neuromorphic architecture

Markov Chain Monte Carlo inference on graphical models using...

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Annual Conference on Information Sciences and Systems (CISS)

作者： Daniel R. Mendat Sang Chin Steve Furber Andreas G. Andreou Department of Electrical and Computer Engineering Johns Hopkins University Baltimore Maryland Applied Physics Laboratory Johns Hopkins University Laurel Maryland School of Computer Science The University of Manchester UK Center for Language and Speech Processing Johns Hopkins University Baltimore Maryland

We present a combined hardware/software architecture to perform Markov Chain Monte Carlo sampling on probabilistic graphical models in a brain-inspired, energy-aware manner. By combining massively-parallel neuromorphic hardware architecture (SpiNNaker) with algorithms we've have developed for the event-based framework employed in SpiNNaker, we achieve large speedups when performing inference as compared to a traditional PC. We present results from two sampling approaches both well suited to the SpiNNaker architecture. Neural sampling, the first of the two approaches relies directly on simulating networks of spiking neurons while the second, Gibb's sampling is more flexible but still takes advantage of the hardware's event-handling capabilities.

关键词： Neurons Graphical models Markov processes Bayes methods Roads computer architecture MATLAB

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