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检索条件"机构=Science and Technology on Blind Signal Processing Laboratory"

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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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Eye movement data modeling using a genetic algorithm

Eye movement data modeling using a genetic algorithm

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Congress on Evolutionary Computation

作者： Yun Zhang Hong Fu Zhen Liang Xiaoyu Zhao Zheru Chi Dagan Feng Xinbo Zhao School of Computer Science Northwestern University Evanston IL USA Center of Multimedia Signal Processing Hong Kong Polytechnic University Hong Kong China School of Information Technologies University of Sydney NSW Australia Key Laboratory of Contemporary Design & Integrated Manufacturing Technology Northwestern Polytechnical University Xi'an Shanxi China

We present a computational model of human eye movements based on a genetic algorithm (GA). The model can generate elemental raw eye movement data in a four-second eye viewing window with a 25 Hz sampling rate. Based on the physiology and psychology characters of human vision system, the fitness function of the GA model is constructed by taking into consideration of five factors including the saliency map, short time memory, saccades distribution, Region of Interest (ROI) map, and a retina model. Our model can produce the scan path of a subject viewing an image, not just several fixations points or artificial ROI's as in the other models. We have also developed both subjective and objective methods to evaluate the model by comparing its behavior with the real eye movement data collected from an eye tracker. Tested on 18 (9 times 2) images from both an obvious-object image group and a non-obvious-object image group, the subjective evaluations shows very close scores between the scan paths generated by the GA model and those real scan paths; for the objective evaluation, experimental results show that the distance between GA's scan paths and human scan paths of the same image has no significant difference by a probability of 78.9% on average.

关键词： Genetic algorithms Humans Computational modeling Sampling methods Physiology Psychology Machine vision Retina Tracking Testing

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Component analysis-based unsupervised linear spectral mixture analysis for hyperspectral imagery

Component analysis-based unsupervised linear spectral mixtur...

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Workshop on Hyperspectral Image and signal processing: Evolution in Remote Sensing, WHISPERS

作者： Xiaoli Jiao Yingzi Du Chein-I Chang Remote Sensing Signal and Image Processing Laboratory Department of Computer Science & Electrical Engineering University of Maryland Baltimore MD USA Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University-Purdue University Indianapolis Indianapolis IN USA Department of Electrical Engineering National Chung Hsing University Taichung Taiwan

One of the most challenging issues in unsupervised linear spectral mixture analysis (LSMA) is how to obtain unknown knowledge of target signatures referred to as virtual endmembers (VEs) directly from the data to be processed. This issue has never arisen in supervised LSMA where the VEs are either assumed to be known a priori or can be provided by visual inspection. With the recent advent of hyperspectral sensor technology many unknown and subtle signal sources can be uncovered and revealed without prior knowledge. This paper addresses this issue and develops a component analysis-based unsupervised LSMA where the desired VEs can be extracted by component analysis-based transforms directly from the data to be processed without appealing for prior knowledge. In order to substantiate the utility of the proposed approach extensive experiments are conducted for demonstration.

关键词： Image analysis Spectral analysis Hyperspectral imaging Independent component analysis Personal communication networks Inspection Statistics signal analysis Hyperspectral sensors Principal component analysis

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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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Effects of terrestrial UV radiation on selected outdoor materials: An interdisciplinary approach

Effects of terrestrial UV radiation on selected outdoor mate...

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SPIE Optical Engineering + Applications

作者： Heikkilä, A. Kazadzis, S. Tolonen-Kivimäki, O. Meinander, O. Lindfors, A. Lakkala, K. Koskela, T. Kaurola, J. Sormanen, A. Kärhä, P. Naula-Iltanen, A. Syrjälä, S. Kaunismaa, M. Juhola, J. Ture, T. Feister, U. Kouremeti, N. Baisb, A. Vilaplana, J.M. Rodriguez, J.J. Guirado, C. Cuevas, E. Koskinen, J. Finnish Meteorological Institute R and D Erik Palménin aukio 1 00560 Helsinki Finland Aristotle University of Thessaloniki Laboratory of Atmospheric Physics 54124 Thessaloniki Greece Helsinki University of Technology Department of Signal Processing and Acoustics Otakaari 5 A 02150 Espoo Finland Tampere University of Technology Department of Materials Science Korkeakoulunkatu 6 33720 Tampere Finland Elastopoli Oy Nokiankatu 1 38210 Sastamala Finland Deutscher Wetterdienst Richard-Assmann-Observatorium Lindenberg Am Observatorium 12 15848 Lindenberg Germany Nacional de Técnica Aeroespacial Estación de Sondeos Atmosféricos El Arenosillo Ctra. San Juan del Puerto - Matalascañas Km.33 21130 Mazagon Huelva Spain Nacional de Meteorologia Spain Observatorio Atmosférico de Izaña C/ La Marina 20 Planta 6 38071 Santa Cruz de Tenerife Spain

ISBN: (纸本)9780819477521

Modern polymeric materials possess an ever increasing potential in a large variety of outdoor objects and structures offering an alternative for many traditional materials. In outdoor applications, however, polymers are subject to a phenomenon called weathering. This is primarily observed as unwanted property changes: yellowing or fading, chalking, blistering, and even severe erosion of the material surface. One of the major weathering factors is UV radiation. In spring 2005, the Finnish Meteorological Institute with its research and industrial partners launched a five-year material research project named UVEMA (UV radiation Effects on MAterials). Within the framework of the project, a weathering network of seven European sites was established. The network extends from the Canary Islands of Spain (latitude 28.5°N) to the Lapland of Finland (latitude 67.4°N), covering a wide range of UV radiation conditions. Since autumn 2005, the sites of the network have been maintaining weathering platforms of specimens of different kinds of polymeric materials. At the same time, the sites have been maintaining their long-term monitoring programmes for spectrally resolved UV radiation. Within UVEMA, these data are used for explaining the differences between the degradation rates of the materials at each site and for correlating the UV conditions in accelerated ageing tests to those under the Sun. We will present the objectives of the UVEMA project aiming at deeper understanding of the ageing of polymers and more reliable assessments for their service life time. Methodologies adopted within the project and the first results of the project will be summarized. © 2009 SPIE.

关键词： Ultraviolet radiation

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Distributed autocorrelation-based sequential detection of OFDM signals in cognitive radios

Distributed autocorrelation-based sequential detection of OF...

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3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008

作者： Chaudhari, Sachin Koivunen, Visa Poor, Vincent H. SMARAD CoE Signal Processing Laboratory Helsinki Univ. of Technology Finland School of Engineering and Applied Science Princeton University

ISBN: (纸本)9781424423026

This paper addresses the problem of collaborative spectrum sensing using sequential detection (SD) in cognitive radios. The goal of sequential processing is to reduce the delay and amount of data needed in identifying underutilized spectrum. Each secondary user (SU) employs a simple and computationally efficient autocorrelation-based detector for Orthogonal Frequency Division Multiplexing (OFDM) signals of the primary user (PU). The decision statistics from individual detectors are combined in a fusion center that may be a separate node or one of the secondary users. The statistical properties of the decision statistics are established. The performance of the scheme is studied by theory and simulations. A comparison of the SD scheme with the Neyman-Pearson Fixed Sample Size (FSS) test for the same false alarm and missed detection probabilities is also carried out.

关键词： Autocorrelation

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Verification algorithm of a sequential circuit's equivalence based on state transfer graph

Verification algorithm of a sequential circuit's equivalence...

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2nd International Symposium on Information Technologies and Applications in Education, ISITAE 2008

作者： Li, Wei Yang, Desheng Lu, Ying Zhang, Yichao Institute of Computer Science and Technology Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9780863419133

An equivalence verification algorithm of sequential circuits [1] based on state transfer graph (STG) is presented in this paper, which obtains some certain useful information through verifying the corresponding state transfer graphs' isomorphism, namely that two corresponding sequential circuits' equivalence . And the verifying includes two steps: firstly, find out all state pairs of the vertexes, which are being verified;secondly verify the equivalence of state pairs, if all the state pairs can be matched as equal state pairs, thus we can come to a conclusion that the corresponding circuits have the same sequential behavior. The algorithm mainly verifies ISCAS85 circuits and some simple state transfer graphs, and the final experiment data shows that the algorithm introduced in the paper will obtain better results compared to BDD(Binary Decision Diagram) and SET(Symbolic Trajectory Evaluation) methods. © 2008 IET.

关键词： Timing circuits

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Optimized calorimeter signal compaction for an independent component based ATLAS electron/jet second-level trigger 12

Optimized calorimeter signal compaction for an independent c...

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12th Advanced Computing and Analysis Techniques in Physics Research, ACAT 2008

作者： Simas Filho, Eduardo F. Seixas, José M. Calôba, Luiz P. Signal Processing Laboratory COPPE/Poli Federal University of Rio de Janeiro Brazil Federal Institute of Education Science and Technology Simões Filho Bahia Brazil

The ATLAS online trigger system has three filtering levels and relies very much on calorimeter information, which is segmented into seven detection layers. Due to differences both in depth and cell granularity of these layers, trigger algorithms may benefit from performing feature extraction at the layer level. This work addresses electron/jet separation at the second level (LVL2) filtering restricted to calorimeter data. Segmented Independent Component Analysis (SICA) is applied over the calorimeter layers in order to extract relevant features for particle identification. The number of independent components to be extracted from a Region of Interest (RoI) is estimated through different signal compaction strategies, such as Principal Component Analysis, Nonlinear Principal Component Analysis and Principal Components for Discrimination. These compaction techniques are evaluated with respect to dimensionality reduction (and processing speed) and classification efficiency. The hypothesis testing is performed by a Multi-Layer Perceptron classifier fed from the segmented independent components. It is shown that the proposed discriminators outperform the baseline design for ATLAS second-level trigger system, achieving a detection efficiency of 99% for a rejection factor smaller than 2%. © 2008 Sissa Medialab Srl. All rights reserved.

关键词： Compaction

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Research and development of signal acquisition unit model

Research and development of signal acquisition unit model

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2nd International Symposium on Information Technologies and Applications in Education, ISITAE 2008

作者： Tao, Baozhuang Zhang, Yichao Lu, Ying Li, Wei Department of Computer Huainan Union University China Institute of Computer Science and Technology Anhui University China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University China

ISBN: (纸本)9780863419133

With core device 8051 Micro-controller and expanding IO-port through Intel 8255A to gather multi-channel signal ,and the final results of data processing are sent out through serial ports. The paper, based on the characteristic of bit operation of 51-serie single-chip and by means of analysis method of mathematical statistics, develops a low-cost, simplestructure, reliable- function and highly efficientalgorithm signal acquisition unit model ,which supplies parallel or serial communication interface and Can be further developed. © 2008 IET.

关键词： Statistics

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Research on the Color Reproduction Based on the BP Neural Network Algorithm

Research on the Color Reproduction Based on the BP Neural Ne...

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International Conference on Advanced Computer Theory and Engineering, ICACTE

作者： Xiao-zhao Xu Xin-feng Zhang Yi-heng Cai Lan-sun Shen Chang-jiang Liu Signal & Information Processing Laboratory Beijing University of Science and Technology Beijing China

This paper proposes an algorithm of BP neural network, which reproduces a color image under D65 light conditions by using a pair of images (one with no D65 light source, and the other with D65 light source). The result of reproduction image which used a fluorescent lamp as an unknown light source is presented. This algorithm successfully removes the effect of the unknown light source color and achieves color constancy at a practical computational cost. The experiment results show that the validity of the proposed algorithm.

关键词： Neural networks Light sources Reflectivity Temperature sensors Color Image sensors Pixel Digital cameras Sensor phenomena and characterization Computer networks

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