检索结果-内蒙古大学图书馆

Detrended cross-correlation analysis of electroencephalogram

Chinese Physics B 2012年第2期21卷 577-580页

作者： Wang Jun Zhao Da-Qing Image Processing and Image Communications Key Laboratory School of Geography and Biological InformationNanjing University of Posts&TelecommunicationNanjing 210003China

In the paper we use detrended cross-correlation analysis （DCCA） to study the electroencephalograms of healthy young subjects and healthy old subjects. It is found that the cross-correlation between different leads of a healthy young subject is larger than that of a healthy old subject. It was shown that the cross-correlation relationship decreases with the aging process and the phenomenon can help to diagnose whether the subject＇s brain function is healthy or not.

关键词： detrended cross-correlation analysis electroencephalogram brain function aging process

来源：评论

学校读者我要写书评

暂无评论

Speech Separation Based on Robust Independent Component Analysis

引用

Chinese Journal of Biomedical Engineering(English Edition) 2013年第4期22卷 169-177页

作者： YAO Wen-po WU Min LIU Tie-bing WANG Jun SHEN Qian Nanjing General Hospital of Nanjing Military Command Image Processing and Image Communications Key Laboratory Nanjing University of Posts & Telecommunications

In this paper, we applied RobustICA to speech separation and made a comprehensive comparison to FastICA according to the separation results. Through a series of speech signal separation test, RobustICA reduced the separation time consumed by FastICA with higher stability, and speeches separated by RobustICA were proved to having lower separation errors. In the 14 groups of speech separation tests, separation time consumed by RobustICA was 3.185 s less than FastICA by nearly 68%. Separation errors of FastICA had a float between 0.004 and 0.02, while the errors of RobustlCA remained around 0.003. Furthermore, compared to FastICA, RobustlCA showed better separation robustness. Experimental results showed that RohustICA was successful to apply to the speech signal separation, and showed superiority to FastlCA in speech separation.

关键词： RobustlCA speech separation FastICA kurtosis optimal step size

来源：评论

学校读者我要写书评

暂无评论

Path planning with danger model immune system

引用

Information Technology Journal 2013年第18期12卷 4659-4665页

作者： Zhao, Lihua Pan, Jin Key Lab of Intelligent Perception and Image Understanding Ministry of Education Xidian University Xi'an 710071 China Xi'an Communications Institute Xi'an 710106 China

In this study, we present a Danger Model immune algorithm based path planning algorithm (DMIA-PP) for robot path planning. Different with the traditional immune algorithm, the system is not based on self-nonself mechanism, but on danger model theory. In a dynamic environment, if the changes of the obstacles affect the found optimal path, a danger signal will be send to the system. And the memory cell will be stimulated to propagate and to mutate, so as to a new optimization circle. The experimental results have shown the effectiveness and accuracy of the method in a complex searching map. © 2013 Asian Network for Scientific Information.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

image representation and recognition based on directed complex network model

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent Systems and Computing 2013年 212卷 985-993页

作者： Chen, Ying Tang, Jin Luo, Bin School of Computer Science and Technology Anhui University Hefei 230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei 230039 China

ISBN: (纸本)9783642375019

image structure representation is a vital technique in the image recognition. A novel image representation and recognition method based on directed complex network is proposed in this paper. Firstly, the key points are extracted from an image as the nodes to construct an initial complete undirected complex network. Then, the k-nearest neighbor evolution method is designed to form a series of directed networks. At last, the feature descriptor of the image is constructed by concatenating the structure features of each directed network to finally achieve image recognition. Experimental results demonstrate that the proposed method outperforms the traditional methods in image recognition and can describe the structure of images more effectively. © Springer-Verlag Berlin Heidelberg 2013.

关键词： image recognition

来源：评论

学校读者我要写书评

暂无评论

THz Spectrum Deconvolution with Total Variation Regularization

THz Spectrum Deconvolution with Total Variation Regularizati...

引用

International Congress on image and Signal processing

作者： Lizhen Deng Hu Zhu Guanming Lu State Key Laboratory of Advanced Electromagnetic Engineering and Technology Huazhong University of Science and Technology Wuhan 430074 China Jiangsu Province Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781479927654

Deconvolution has become one of the most used methods for improving spectral resolution, and blind deconvolution as a typical method has been researched widely. However, the predefined point spread function (PSF) used in blind deconvolution method is not known exactly in practice. In general, the PSF is estimated simultaneously from the observed spectrum, but it becomes difficult when the spectroscopic data are polluted by strong noise. In this paper, we present a deconvolution method used to improve the resolution of THz spectrum. In the method, the energy function is constructed, which includes the likelihood term, Total variation of spectrum term and L2 norm of the PSF term. The PSF is modeled as a parametric function combination with the a priori knowledge about the characteristics of the instrumental response. The spectrum and the parameter of PSF are obtained by minimizing the energy functional using alternate minimization approach. Experimental results are shown to demonstrate the efficiency of the proposed method used for THz spectrum.

关键词： THz spectrum Total variation deconvolution alternate minimization approach

来源：评论

学校读者我要写书评

暂无评论

Video Summarization by Robust Low-Rank Subspace Segmentation

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent Systems and Computing 2013年 212卷 929-937页

作者： Tu, Zhengzheng Sun, Dengdi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei 230039 China School of Computer Science and Technology Anhui University Hefei 230601 China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei 230039 China

ISBN: (纸本)9783642375019

Video summarization provides condensed and succinct representations of the content of a video stream. A static storyboard summarization approach based on robust low-rank subspace segmentation is proposed in this paper. Firstly, video frames are represented as multi-dimensional vectors, and then embedded into a group of affine subspaces using low-rank representation according to the content similarity of the frames in the same subspace. Secondly, a series of subspaces are segmented based on the Normalized Cuts algorithm. The video summary is finally generated by choosing key frames from the significant subspaces and ranking these key frames in temporal order. The experimental results demonstrate that the proposed summarization algorithm can produce crucial key frames and effectively reduce the visual content redundancy in summary comparing with the conventional approaches. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Vectors

来源：评论

学校读者我要写书评

暂无评论

A Local Elitism Based Membrane Evolutionary Algorithm for Point Pattern Matching

Advances in Intelligent Systems and Computing

引用

Advances in Intelligent Systems and Computing 2013年 212卷 873-882页

作者： Ding, Zhuanlian Tang, Jin Zhang, Xingyi Luo, Bin School of Computer Science and Technology Anhui University Hefei 230601 Anhui China Key Lab of Industrial Image Processing and Analysis of Anhui Province Hefei 230039 Anhui China

ISBN: (纸本)9783642375019

Point pattern matching is a fundamental problem in computer vision and pattern recognition. Membrane computing is an emergent branch of bio-inspired computing, which provides a novel idea to solve computationally hard problems. In this paper, a new point pattern matching algorithm with local elitism strategy is proposed based on membrane computing models. Local elitism strategy is used to keep good correspondences of point pattern matching found during the search, so the matching rate and the convergence speed are improved. Five heuristic mutation rules are introduced to avoid the local optimum. Experiment results on both synthetic data and real world data illustrate that the proposed algorithm is of higher matching rate and better stability. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Membranes

来源：评论

学校读者我要写书评

暂无评论

SAR image multiclass segmentation using a multiscale and multidirection triplet Markov fields model in nonsubsampled contourlet transform domain

引用

Information Fusion 2013年第4期14卷 441-449页

作者： Yan Wu Peng Zhang Ming Li Qiang Zhang Fan Wang Lu Jia Remote Sensing Image Processing and Fusion Group School of Electronic Engineering Xidian University P.O. Box 140 Xi’an Shaanxi 710071 China National Key Lab. of Radar Signal Processing Xidian University Xi’an 710071 China

Triplet Markov fields (TMFs) model recently proposed is to deal with nonstationary image segmentation and has achieved promising results. In this paper, we propose a multiscale and multidirection TMF model for nonstationary synthetic aperture radar (SAR) image multiclass segmentation in nonsubsampled contourlet transform (NSCT) domain, named as NSCT-TMF model. NSCT-TMF model is capable of capturing the contextual information of image content in the spatial and scale spaces effectively by the construction of multiscale energy functions. And the derived multiscale and multidirection likelihoods of NSCT-TMF model can capture the dependencies of NSCT coefficients across scale and directions. In this way, the proposed model is able to achieve multiscale information fusion in terms of image configuration and features in underlying labeling process. Experimental results demonstrate that due to the effective propagation of the contextual information, NSCT-TMF model turns out to be more robust against speckle noise and improves the performance of nonstationary SAR image segmentation.

关键词： SAR image multiclass segmentation NSCT-TMF model NSCT-HMT NSCT-TMF energy function Multiscale information fusion

来源：评论

学校读者我要写书评

暂无评论

image Demosaicing by Non-local Similarity and Local Correlation

Image Demosaicing by Non-local Similarity and Local Correlat...

引用

2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Wang Guo-gang Zhu Xiu-chang Gan Zong-liang Province Key Lab on Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Conventional single-chip digital cameras use color filter arrays(CFA) to sample different spectral components. image demosaicing is a problem of interpolating these data to complete red, green, and blue values for each image pixel, to produce an RGB image. Many color demosaicing(CDM) methods assume that the high local spatial redundancy exists among the color samples. Such an assumption, however, may be fail for images with high color saturation and sharp color transitions. This paper presents an adaptive demosaicing algorithm by exploiting both the non-local similarity and the local correlation(NLS-LC) in the color filter array image. First, the most flattest nonlocal image patches are searched in the searching window centered on the estimated pixel. Second, the patch, which is the most similar to the current patch, is selected among the most smoothest nonlocal patches. Third, according to the similar degree and the local correlation degree, the obtained nonlocal image patch and the current patch are adaptively chosen to estimate the missing color samples. Experimental results indicate that the proposed method exhibits superior performance over many state-of-the-art color interpolation methods.

关键词： image demosaicing, image interpolation, local correlation, non-local similarity

来源：评论

学校读者我要写书评

暂无评论

Free Viewpoint Action Recognition based on Self-similarities

Free Viewpoint Action Recognition based on Self-similarities

引用

2012 IEEE 11th International Conference on Signal processing(ICSP 2012)

作者： Jiao Wang Changhong Chen Xiuchang Zhu Jiangsu Provincial Key Lab of Image Processing and Image Communication Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781467321969

Action recognition is an important topic in computer vision and most current work focuses on view-dependent representations. In this paper, we develop a novel free viewpoint action recognition based on Self-similarity matrix (SSM), which tends to be stable across views. We choose Local Self-similarity (LSS) descriptor as our low-level feature, then SSM is calculated by computing the similarity between any pair of frame features. Each video sequence is represented using a diagonal descriptor vector extracted from the SSM. Support Vector Machines (SVM) is employed for classification. The encouraging experimental results on the public IXMAS multi-view data set demonstrate effectiveness of the proposed method.

关键词： local self-similarity descriptor self-similarity matrix diagonal feature action recognition view independent

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：