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IEEE International Symposium on Intelligent signal processing and Communication Systems (ISPACS)

作者： Nattachai Watcharapinchai Supavadee Aramvith Supakorn Siddhichai Sanparith Marukatat Digital Signal Processing Research Laboratory Department of Electrical Engineering Chulalongkom University Bangkok Thailand National Electronics and Computer Technology Center Pathumthani Thailand

The problem of automatic object categorization is investigated under the proposed bag of feature object categorization framework. The framework consists of feature detection and representation which uses the scale invariant feature transform (SIFT) as local feature and bag of feature model to represent the image. Learning process utilizes k-NN (k-nearest neighbour). In this paper, we propose the dimensionality reduction of SIFT using principal component analysis (PCA) on each object category to reduce computational complexity and memory requirement during training process. Experimental results show that our proposed technique can reduce the dimension of SIFT up to around 80% with the same average precision compared to baseline technique without our proposed method.

关键词： Principal component analysis computer vision Histograms Digital signal processing Computational complexity Video compression Testing Training data Vocabulary Feature extraction

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Editorial: Game theory in signal processing and communications

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Eurasip Journal on Advances in signal processing 2009年 2009卷

作者： Jorswieck, Eduard A. Boche, Holger Han, Zhu Larsson, Erik G. Department of Mobile Communications School of Electrical Engineering and Computer Sciences Technical University of Berlin Berlin Germany Wireless Networking Signal Processing and Security Lab Department of Electrical and Computer Engineering University of Houston Houston TX 77004 United States Linkping University SE-581 83 Linkping Sweden Communications Laboratory Faculty of Electrical Engineering and Information Technology Dresden University of Technology 01062 Dresden Germany

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Joint user scheduling and beamforming for underlay cognitive radio systems

Joint user scheduling and beamforming for underlay cognitive...

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Asia-Pacific Conference on communications

作者： Wenhui Zong Sen Shao Qingmin Meng Weiping Zhu Institute of Signal and Transmission Nanjing University of Posts and Telecommunications Nanjing China National Mobile Communications Research Laboratory South-East University Nanjing China Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

ISBN: (纸本)9781424447848

In this paper, we consider underlay cognitive radio systems in which secondary users coexist with users in primary networks whose radio band is licensed. The secondary subnetwork comprising the cognitive users utilizes the cognitive radio technology to make opportunistic access to the licensed spectrum that primary users own. In this scheme, we discuss the issue of joint user scheduling and beamforming in order to make sure that received interferences at the primary users maintain below an affordable threshold level. The user scheduling includes two procedures: 1) primary users scheduling; 2) secondary users scheduling. However, these two steps are carried out coordinately and the selected primary user and corresponding cognitive users can be obtained. In addition, Zero-forcing Beamforming (ZFBF) and antenna selection are integrated into our scheme where the former is used to support multiple concurrent streams transmission and the latter is used to reduce the feedback in the uplink of the secondary system. Our performance results show that the proposed scheme can significantly improve the throughput of the whole cognitive radio networks.

关键词： Array signal processing Cognitive radio Mobile communication Wireless communication Interference constraints Receiving antennas Downlink signal processing Transmitting antennas Throughput

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A Near Fair User Scheduling Scheme in Cognitive Radio Networks

A Near Fair User Scheduling Scheme in Cognitive Radio Networ...

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International Conference on Wireless communications, Networking and Mobile Computing (WiCom)

作者： Qingmin Meng Wenhui Zong Sen Shao Weiping Zhu Baoyu Zheng National Mobile Communications Research Laboratory South-East University Nanjing China Institute of Signal and Transmission Nanjing University of Posts and Telecommunications Nanjing China Centre of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

Nowadays, cognitive radio technique has been acknowledged as a smart and potential method to improve the spectrum utilization. In this work, we investigate a cognitive radio communication scheme, where a number of cognitive users, each with multiple antennas, can share the spectrum with the primary user. To decrease the inter-user interference, zero-forcing beamforming (ZFBF) is considered. We presented a design of three-step selection for both the cognitive users and their antennas at receiver. In the first step of the studied scheme, antennas-selection is performed to based on a certain algorithm and then user-selection is performed based on Proportional Fair algorithm. Next the active set of cognitive users is selected according to the correlation between the users in the third step. Simulation results show that at the expense of some sum-rate loss, our proposed scheme can realize near fair resource allocation among the cognitive users as well as the decrease of the interference to the primary user and of the feedback.

关键词： Cognitive radio Receiving antennas Interference Downlink Scheduling Antenna feeds Base stations signal processing Mobile communication Array signal processing

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Brain tissue classification using independent vector analysis (IVA) for magnetic resonance image

Brain tissue classification using independent vector analysi...

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2009 9th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2009

作者： Chiou, Yaw-Jiunn Chen, Hsiang-Min Chai, Jyh Wen Chen, Clayton Chi-Chang Ouyang, Yen-Chieh Su, Wu-Chung Yang, Ching-Wen Lee, San-Kan Chang, Chein-I. Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology College of Medicine China Medical University Taichung Taiwan School of Medicine National Yang-Ming University Taipei Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Computer Center Taichung Veterans General Hospital Taichung 407 Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States

ISBN: (纸本)9780769536569

The purpose of this study is to present a new method, independent vector analysis (IVA), by extending independent component analysis (ICA) of univariate source signals to multivariate source signals on Magnetic Resonance Imaging (MRI). IVA is utilized to relief the limitation of the conventional ICA approach. The proposed method can resolve the permutation problem during individual ICA runs for group brain MR images. The proposed IVA method in conjunction with support vector machine (SVM), we can effectively separate the different part of gray, white matter and cerebrospinal fluid (CSF) from brain soft tissues. In order to demonstrate the proposed IVA-SVM method, experiments are conducted for performance analysis and evaluation. Simulation results show that using IVA can greatly release from the problem cause from traditional ICA to the situation of analyzing inconsistent results of MR image. © 2009 IEEE.

关键词： Magnetic resonance imaging

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An automatic computer-aided detection system for meniscal tears on magnetic resonance images

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IEEE Transactions on Medical Imaging 2009年第8期28卷 1308-1316页

作者： Ramakrishna, Bharath Liu, Weimin Saiprasad, Ganesh Safdar, Nabile Chang, Chein-I Siddiqui, Khan Kim, W. Siegel, Eliot Chai, Jyh-Wen Chen, Clayton Chi-Chang Lee, San-Kan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD 21250 United States University of Maryland School of Medicine Baltimore MD 21201 United States Department of Electrical Engineering and Environmental Restoration Disaster Reduction Research Center National Chung Hsing University Taichung 402 Taiwan VA Maryland Health Care System Baltimore MD 21201 United States Hospital of the University of Pennsylvania Philadelphia PA 19104 United States Department of Radiology College of Medicine China Medical University Taichung 404 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 40705 Taiwan Department of Radiological Technology Central Taiwan University of Science and Technology Taichung 406 Taiwan Department of Radiology Taichung Veterans General Hospital Taichung 407 Taiwan

Knee-related injuries including meniscal tears are common in both young athletes and the aging population, and require accurate diagnosis and surgical intervention when appropriate. With proper techniques and radiologists' experienced skills, confidence in detection of meniscal tears can be quite high. This paper develops a novel computer-aided detection (CAD) diagnostic system for automatic detection of meniscal tears in the knee. Evaluation of this CAD system using an archived database of images from 40 individuals with suspected knee injuries indicates that the sensitivity and specificity of the proposed CAD system are 83.87% and 75.19%, respectively, compared to the mean sensitivity and specificity of 77.41% and 81.39%, respectively, obtained by experienced radiologists in routine diagnosis without using the CAD. The experimental results suggest that the developed CAD system has great potential and promise in automatic detection of both simple and complex meniscal tears of the knee. © 2009 IEEE.

关键词： Magnetic resonance imaging

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A new method for characterization of coronary plaque composition via IVUS images

A new method for characterization of coronary plaque composi...

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IEEE International Symposium on Biomedical Imaging

作者： Arash Taki Alireza Roodaki Olivier Pauly S. K. Setarehdan Gozde Unal Nassir Navab Department of Computer Aided Medical Procedures (CAMP) Technical University Munich Munich Germany Department of Signal Processing and Electronic Systems Supelec Gif-sur-Yvette France Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Faculty of Engineering and Natural Sciences Sabanci University Turkey

ISBN: (纸本)9781424439317

IVUS-derived virtual histology (VH) permits the assessment of atherosclerotic plaque morphology by using radiofrequency analysis of ultrasound signals. However, it requires the acquisition to be ECG-gated, which is a major limitation of VH. Indeed, its computation can only be performed once per cardiac cycle, which significantly decreases the longitudinal resolution of VH. To overcome this limitation, the introduction of an image-based plaque characterization is of great importance. Current IVUS image processing techniques do not allow adequate identification of the coronary artery plaques. This can be improved by defining appropriate features for the different kinds of plaques. In this paper, a novel feature extraction method based on Run-length algorithm is presented and used for improving the automated characterization of the plaques within the IVUS images. The proposed feature extraction method is applied to 200 IVUS images obtained from five patients. As a result an accuracy rate of 77% was achieved. Comparing this to the accuracy rates of 75% and 71% obtained using co-occurrence and local binary pattern methods respectively indicates the superior performance of the proposed feature extraction method.

关键词： Feature extraction Gray-scale Biomedical engineering Radio frequency Image resolution signal processing signal analysis Ultrasonic imaging signal resolution Arteries

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Correlations in underwater acoustic particle velocity and pressure channels

Correlations in underwater acoustic particle velocity and pr...

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Annual Conference on Information Sciences and Systems (CISS)

作者： H. Guo A. Abdi A. Song M. Badiey Department of Electrical and Computer Engineering Center of Wireless Communication and Signal Processing Research New Jersey Institute of Technology Newark NJ USA Physical Ocean Science and Engineering College of Marine and Earth Studies University of Delaware Newark DE USA

Depending on the angle of arrivals (AOAs) and other channel characteristics, different types of correlation appear among acoustic pressure and acoustic particle velocity channels. To have accurate channel models for communication system design, a complete set of correlations are derived in this paper for a vector sensor array. In addition to exact results, accurate yet less complex approximations are derived as well. Based on the exact correlations, delay spread of pressure and particle velocity channels are calculated as well.

关键词： Underwater acoustics Sensor arrays Acoustic sensors Sensor phenomena and characterization Frequency Delay Velocity measurement Pressure measurement Acoustical engineering Sensor systems

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Design optimization for 10gb/s full-duplex transmission using RSOA-based ONU with electrical and optical filtering and equalization

Design optimization for 10gb/s full-duplex transmission usin...

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European Conference on Optical Communication (ECOC)

作者： M. Omella I. Papagiannakis D. Klonidis J.A. Lazaro A.N. Birbas J. Kikidis I. Tomkos J. Prat Signal Theory & Communications Department (TSC) UPC Barcelona Tech Spain Electrical & Computer Engineering Department University of Patras Patras Greece Athens Information Technology Center Athens Greece Analog Integrated Electronic Systems S. A. Greece

The optimum design characteristics to maximize the performance of 10 Gbps full-duplex bidirectional transmission are studied experimentally using a low-bandwidth RSOA assisted by electronic equalization and optimum fi... 详细信息

关键词： Optical filters Design optimization Optical network units Filtering Optical receivers Optical attenuators Passive optical networks Optical noise Band pass filters Bandwidth

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Brain Tissue Classification Using Independent Vector Analysis (IVA) for Magnetic Resonance Image

Brain Tissue Classification Using Independent Vector Analysi...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yaw-Jiunn Chiou Hsiang-Min Chen Jyh Wen Chai Clayton Chi-Chang Chen Yen-Chieh Ouyang Wu-Chung Su Ching-Wen Yang San-Kan Lee Chein-I Chang Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Department of Radiology College of Medicine China Medical University and Hospital Taichung Taiwan Department of Radiology Taichung Veterans General Hospital Taichung Taiwan Department of Radiological Technology Central Taiwan University of Science and technology Taichung Taiwan Computer Center Taichung Veterans General Hospital Taichung Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD USA

关键词： Brain Image analysis Magnetic analysis Magnetic resonance Independent component analysis Magnetic resonance imaging Support vector machines signal analysis Image resolution signal resolution

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