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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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Perceptual Contrast-Based Image Fusion: A Variational Approach

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自动化学报 2007年第2期33卷 132-137页

作者： WANG Chao YE Zhong-Fu Institute of Statistical Signal Processing Department of Electrical Engineering and Information Science University of Science and Technology of China Hefei 230027 P.R.China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 P.R.China

本地对比，或变化，在主要是从来源图象保存重要信息到熔化结果的图象熔化起一个重要作用。威伯的法律告诉我们在不同背景下面的一样的变化将引起不同感性的感情，因此，一个理想的图象处理器不得不考虑视觉心理学和心物学的效果。这份... 详细信息

本地对比，或变化，在主要是从来源图象保存重要信息到熔化结果的图象熔化起一个重要作用。威伯的法律告诉我们在不同背景下面的一样的变化将引起不同感性的感情，因此，一个理想的图象处理器不得不考虑视觉心理学和心物学的效果。这份报纸考虑人的视觉系统(HVS ) 的性质并且从每幅来源图象把量的感性的变化转移到结果。把 just-noticeable-difference (JND ) 用作测量， multiband 图象的感性的对比作为一个目标被获得。我们构造一个功能的极值问题发现一幅单身的乐队图象，或熔化结果，它有最近感性的对比到目标一个。经由变化途径， Euler-Lagrange 方程被导出，并且一次坡度降下重复被采用。试验性的结果证明这个方法感性地好。

关键词：表象聚变变化方法知觉衬比度 HVS PDES 人工智能

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Wavelet-based despeckling of SAR images using Gauss-Markov random fields

Wavelet-based despeckling of SAR images using Gauss-Markov r...

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作者： Gleich, Dušan Datcu, Mihai IEEE Laboratory for Signal Processing and Remote Control Faculty of Electrical Engineering and Computer Science University of Maribor 2000 Maribor Slovenia Remote Sensing Technology Institute IMF 82234 Weßling Germany Paris Institute of Technology GET Telecom Paris University Politechnica of Bucharest Bucharest Romania

In this paper, a wavelet-based speckle-removing algorithm is represented and tested on synthetic aperture radar (SAR) images. The SAR image is first transformed using a dyadic wavelet transform. The noise in the wavelet-transformed image is modeled as an additive signal-dependent noise with Gaussian distribution. The distribution of a noise-free image in a wavelet domain is modeled as a generalized Gauss-Markov random field (GGMRF). An unsupervised stochastic model-based approach to image denoising is represented. If the observed area is homogeneous, the parameters of the Gaussian distribution and GGMRFs are estimated from incomplete data using mixtures of wavelet coefficients. An expectation-maximization algorithm is used to estimate the parameters of both noisy and noise-free images. The unknown parameters are estimated using image and noise models that are defined in the wavelet domain for heterogeneous areas. Different inter- and intrascale dependences of wavelet coefficients were used to estimate the unknown parameters. The represented wavelet-based method efficiently removes noise from SAR images. © 2007 IEEE.

关键词： Radar imaging

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A method of multi-user detection based on Independent Component Analysis for DS-CDMA systems

A method of multi-user detection based on Independent Compon...

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2007 IET Conference on Wireless, Mobile and Sensor Networks (CCWMSN07)

作者： X. H. Li W. Gao Y. Cheng The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Electronic Science and Technology Anhui University Hefei China

The DS-CDMA signal model and the noisy linear independent component analysis (ICA) model are analyzed in this paper. Comparing these models shows that they have the same form. The adaptive minimum mean-square error (MMSE) multiuse detection based on ICA is proposed. It uses the output of adaptive MMSE multi-user detection to initialize the ICA iterations, not only the known spread information of interesting user is used to overcome the uncertainness of ICA, but also the character of statistical independence is used. The simulation results show that the performance is improved obviously.

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A Novel Representation of Concept Hierarchy Based on Quotient Space Model

A Novel Representation of Concept Hierarchy Based on Quotien...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Xue-jun Li Long-shu Li Ling Zhang Yi Xu Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui University of Science and Technology Hefei China School of Computer Science and Technology Anhui University of Science and Technology Hefei China

Concept hierarchies are important in many generalized data mining applications, such as multiple-level fuzzy association rule mining. Usually concept hierarchies are given by domain experts. However, it is extremely difficult and time-consuming for human experts to discover concepts and construct concept hierarchies from the domain. In literature, several representations of concept hierarchy are possible, for example tree, lattice, table, linked list, arbitrary graph etc. In this paper, we apply quotient space model to representing concept hierarchies. In contrast to others, the representation model is much more extensible and compatible. The results indicate that this technique can improve the efficiency of performing the generalization and specialization operation in concept hierarchies.

关键词： Databases Data mining Tree graphs Cities and towns Space technology Lattices Laboratories Competitive intelligence signal processing Educational technology

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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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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

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

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: a i,1 P 1 + a i,2 P 2 + hellip + a i,t P t 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.

关键词： Elliptic curve cryptography Equations Artificial intelligence Distributed computing Elliptic curves Public key cryptography Software engineering Laboratories Intelligent networks Computer networks

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Fuzzy Clustering Ensemble Based on Dual Boosting

Fuzzy Clustering Ensemble Based on Dual Boosting

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Su-lan Zhai Bin Luo Yu-tang Guo School of Mathematics and Computing Anhui University of Science and Technology Hefei China Key Laboratory of Intelligent Computing Signal Processing of Anhui University Hefei China

It is widely recognized that clustering ensemble is fit for any shape and any distribution dataset and that the boosting method provides superior results for classification problems. In the paper, a dual boosting is proposed for fuzzy clustering ensemble . At each boosting iteration, a new training set is created based on the original datasets' probability which is associated with the previous clustering. According to the dual boosting method, the new training subset contains not only the instances which is hard to cluster in previous stages , but also the instances which is easy to cluster. The final clustering solution is produced by using the clustering based on the co-association matrix. Experiments on both artificial and realworld datasets demonstrate the efficiency of the fuzzy clustering ensemble based on dual boosting in stability and accuracy.

关键词： Boosting Clustering algorithms signal processing algorithms Partitioning algorithms Laboratories Mathematics signal processing Shape measurement Robustness Bagging

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