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Advances in nonnegative matrix and tensor factorization

Computational Intelligence and Neuroscience 2008年第1期2008卷 852187页

作者： Wang, W. Cichocki, A. Mørup, M. Smaragdis, P. Zdunek, R. Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Saitama 351-0198 Japan Department of Informatics and Mathematical Modeling Technical University of Denmark Building 321 2800 Lyngby Richard Petersens Plads Denmark Advanced Technology Labs. Adobe Systems Inc. Newton MA 02466 275 Grove Street United States Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH United Kingdom Institute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology Wybrzeze 50370 Wroclaw Wyspianskiego 27 Poland

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Fast nonnegative matrix factorization algorithms using projected gradient approaches for large-scale problems

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Computational Intelligence and Neuroscience 2008年第1期2008卷 939567页

作者： Zdunek, Rafal Cichocki, Andrzej Instiute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology 50-370 Wroclaw Wybrzeze Wyspianskiego 27 Poland Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Wako-shi Saitama 351-0198 Japan Institute of Theory of Electrical Engineering Measurement and Information Systems Faculty of Electrical Engineering Warsaw University of Technology 00-661 Warsaw Poland Systems Research Institute Polish Academy of Science (PAN) 01-447 Warsaw Poland

Recently, a considerable growth of interest in projected gradient (PG) methods has been observed due to their high efficiency in solving large-scale convex minimization problems subject to linear constraints. Since the minimization problems underlying nonnegative matrix factorization (NMF) of large matrices well matches this class of minimization problems, we investigate and test some recent PG methods in the context of their applicability to NMF. In particular, the paper focuses on the following modified methods: projected Landweber, Barzilai-Borwein gradient projection, projected sequential subspace optimization (PSESOP), interior-point Newton (IPN), and sequential coordinate-wise. The proposed and implemented NMF PG algorithms are compared with respect to their performance in terms of signal-to-interference ratio (SIR) and elapsed time, using a simple benchmark of mixed partially dependent nonnegative signals.

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In time passive localization using multi base-line phase comparison receivers

In time passive localization using multi base-line phase com...

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2006 CIE International Conference on Radar, ICR 2006

作者： Wei, Xing Wan, Jian-Wei Huangfu, Kan Laboratory of Digital Signal Processing School of Electronic Science and Engineering National Univ. of Defense Technology Changsha 410073 China

ISBN: (纸本)0780395824

A new in time passive localization system based on multi base-line phase comparison receivers is proposed. The new system uses short base-line to avoid the long base-line phase illegibility then uses the phase differences without illegibility to get the signal arriving angle and to detect the emitter's range. The GDOP and Simulation performance have also been discussed in this paper. © 2006 IEEE.

关键词： Radar receivers

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Image Segmentation Based on Modified Pulse-Coupled Neural Networks

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电子学报(英文版) 2007年第1期16卷 119-122页

作者： ZHANG Junying FAN Xiuju DONG Jiyang SHI Meihong School of Computer Science and Engineering Xidian University Xi＇an 710071 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Information and Control Department Xi＇an Engineering Science and Technology Institute Xi＇an 710048 Chian

Based on the property of Human vision system (HVS) that human eye's sensitivity to an image varies with different information regions of the image, Pulse-coupled neural network (PCNN) model is modified for image segmentation. The modified PCNN stimulated by an input image has pulse output with multiple pulse values rather than only two in the conventional PCNN, according to the local information rate of the input image. This results in image segmentation according to local information rate delivered from the image by the modified PCNN. Experiments with the modified PCNN on image segmentation and image compression on the segmented images with the principle that the lower information rate is, the higher compression rate is applied, show much better performance in compression rate compared with that on the segmented images with the conventional PCNN.

关键词：脉冲耦合神经网络图象分割图象压缩数学模型改进

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COMPUTER SIMULATION OF RAYLEIGH FADING CHANNELS IN MC-CDMA SYSTEMS

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Journal of Electronics(China) 2007年第5期24卷 577-582页

作者： Han Fangming Zhang Xianda National Laboratory of Radar Signal Processing Xidian University Xi＇an 710071 China National Laboratory of Tsinghua Information Science and Technology Department of AutomationTsinghua University Beijing 100084 China

For Multi-Carrier-Code Division Multiple Access （MC-CDMA） systems, it is usually assumed that the fading of the subcarriers is frequency non-selective and independent of each other. This paper shows that the two assumptions are incompatible. In fact, the MC-CDMA signals at each subcarrier undergo fading that are highly correlated. Based on this observation, this paper develops a simulation algorithm for Rayleigh fading channels via frequency-domain correlation functionl which incorporates the Doppler effect simultaneously. Numerical examples are presented to demonstrate the effectiveness of the new algorithm, with the conclusion that the independence assumption of subcarrier fading overrates the system performance.

关键词： Multi-Carrier-Code Division Multiple Access （MC-CDMA） Rayleigh fading Channelsimulation Frequency-domain correlation

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A cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks

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Frontiers of Electrical and Electronic Engineering in China 2007年第2期2卷 219-229页

作者： ZHENG Xiangquan GUO Wei GE Lijia LIU Renting Key Laboratory of Digital Communication and Signal Processing Chongqing Communication CollegeChongqing 400035China National Key Laboratory of Communication University of Electronic Science and Technology of ChinaChengdu 610054China

In order to periodically reassess the status of the alternate path route(APR)set and to improve the efficiency of alternate path construction existing in most current alter-nate path routing protocols,we present a cross-layer design and ant-colony optimization based load-balancing routing protocol for ad-hoc networks(CALRA)in this *** CALRA,the APR set maintained in nodes is aged and reas-sessed by the inherent mechanism of pheromone evaporation of ant-colony optimization algorithm,and load balance of network is achieved by ant-colony optimization combining with cross-layer synthetic *** efficiency of APR set construction is improved by bidirectional and hop-by-hop routing update during routing discovery and routing maintenance ***,ants in CALRA deposit simulated pheromones as a function of multiple parameters corresponding to the information collected by each layer of each node visited,such as the distance from their source node,the congestion degree of the visited nodes,the current pheromones the nodes possess,the velocity of the nodes,and so on,and provide the information to the visiting nodes to update their pheromone tables by endowing the different parameters corresponding to different information and different weight values,which provides a new method to improve the congestion problem,the shortcut problem,the convergence rate and the heavy overheads commonly existed in existing ant-based routing protocols for ad-hoc *** performance of the algorithm is measured by the packet delivery rate,good-put ratio(routing overhead),and end-to-end *** results show that CALRA performs well in decreasing the route overheads,balancing traffic load,as well as increasing the packet delivery rate,etc.

关键词： cross-layer design ant-colony optimization load-balancing routing protocol APR

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Multichannel EEG brain activity pattern analysis in time-frequency domain with nonnegative matrix factorization support

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International Congress Series 2007年 1301卷 266-269页

作者： Rutkowski, Tomasz M. Zdunek, Rafal Cichocki, Andrzej Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Japan Institute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology Poland Warsaw University of Technology Poland

A novel approach combining a time-frequency representation of brain activity in the form of recorded EEG signals together with nonnegative matrix factorization (NMF) post-processing section in brain computer interface (BCI) training paradigm is presented. Such a combination of two emerging signal analysis techniques enables us to find and enhance very small oscillations related to presented visual stimuli. Presented results confirm validity of the chosen approach. © 2007 Elsevier B.V. All rights reserved.

关键词： Brain computer interface EEG EEG analysis Empirical mode decomposition Nonnegative matrix factorization Time-frequency signal analysis

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A (t, n)-threshold verified multi-secret sharing scheme based on ECDLP

A (t, n)-threshold verified multi-secret sharing scheme base...

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SNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing

作者： Runhua, Shi Hong, Zhong Liusheng, Huang Key Laboratory of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei 230039 China Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China

ISBN: (纸本)0769529097

In this article, we propose a (t,n) threshold verifiable multi-secret sharing scheme, in which to reconstruct t secrets needs to solve t simultaneous equations. The analysis results show that our scheme is as easy as Yang's scheme [8] in the secret reconstruction and requires less public values than Chien's [7] and Yang's schemes. Furthermore, the shares in our scheme can be verified their validity with t public values based on ECDLP, and there are two verified forms: one is computationally secure as Feldman 's scheme [12] and other is unconditionally secure as Pedersen 's scheme [13]. In addition, for the main computation: ai,1P1 + ai,2P2 + + ai,tPt in our scheme, we present a new method based on the signed factorial expansion and implement it, the results show that it is more efficient than the current public methods. Thus our scheme is a secure and efficient (t,n) threshold verified multi-secret sharing scheme. © 2007 IEEE.

关键词： Threshold logic

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Bearing vibration signal analysis based on chirplet transform

Bearing vibration signal analysis based on chirplet transfor...

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2007 8th International Conference on Electronic Measurement and Instruments, ICEMI

作者： Gao, Qingwei Lu, Yixiang Zhao, Yanfei Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Institute of Electronic Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)1424411351

A method based on the fast adaptive chirplet transform is presented for bearing vibration signal analysis. Based on parameters coarse estimation, it converts multi-dimension optimization process to a traditional curve-fitting problem. This method is not only free of cross-term interference, but also maintains good time-frequency resolution. In addition, as a result of fewer inner product calculations are conducted, the computational speed is fast and parameters estimation is more accurate. The experimental results show that the algorithm can efficiently extract the time-frequency characteristics of the fault signals, and the effect is better than other time-frequency methods. Therefore, it is an efficient fault diagnosis method. © 2007 IEEE.

关键词： Vibration analysis

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Development of Alzheimer's Disease Recognition using Semiautomatic Analysis of Statistical Parameters based on Frequency Characteristics of Medical Images

Development of Alzheimer's Disease Recognition using Semiaut...

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IEEE International Conference on signal processing and Communications, ICSPC

作者： Meysam Torabi Hassan Moradzadeh Reza Vaziri S. Mohammad Javad Razavian Reza Dehestani Ardekani Moones Rahmandoust Ali Taalimi Emad Fatemizadeh Sharif University of Technology Iran Iran University of Science and Technology Iran Biomedical Signal and Image Processing Laboratory Sharif University of Technology Iran Biomedical Signal and Image Processing Laboratory Kashan University Iran

The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's disease (AD) which appeared in patient's brain. The features of interest are categorized in features of the spatial domain (FSD's) and Features of the frequency domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer perceptron artificial neural network (ANN). Before ANN, the number of features is reduced from 44 to 12 to optimize and eliminate any correlation between them. The contribution of this paper is to demonstrate that by using the wavelet transform number of features needed for AD diagnosis has been reduced in comparison with the previous work. We achieved 79% and 100% accuracy among test set and training set respectively, including 93 MR-images.

关键词： Alzheimer's disease Character recognition Image recognition Image analysis Frequency Biomedical imaging Artificial neural networks Wavelet transforms Medical diagnostic imaging Algorithm design and analysis

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