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mutual-information based weighted fusion for target tracking in underwater wireless sensor networks

Frontiers of information Technology & Electronic Engineering 2018年第4期19卷 544-556页

作者： Duo ZHANG Mei-qin LIU Sen-lin ZHANG Zhen FAN Qun-fei ZHANG State Key Laboratory of Industrial Control Technology Zhejiang University College of Electrical Engineering Zhejiang University School of Marine Science and Technology Northwestern Polytechnical University

Underwater wireless sensor networks(UWSNs)can provide a promising solution to underwater target *** to limited energy and bandwidth resources,only a small number of nodes are selected to track a target at each *** all measurements are fused together to provide information in a fusion center,fusion weights of all selected nodes may affect the performance of target *** far as we know,almost all existing tracking schemes neglect this *** study a weighted fusion scheme for target tracking in ***,because the mutual information(MI)between a node’s measurement and the target state can quantify target information provided by the node,it is calculated to determine proper fusion ***,we design a novel multi-sensor weighted particle filter(MSWPF)using fusion weights determined by ***,we present a local node selection scheme based on posterior Cramer-Rao lower bound(PCRLB)to improve tracking ***,simulation results are presented to verify the performance improvement of our scheme with proper fusion weights.

关键词： Target tacking Fusion weight mutual information Node selection Underwater wireless sensor networks

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Partial mutual information for Input Selection of Time Series Prediction

Partial Mutual Information for Input Selection of Time Serie...

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2011 Chinese Control and Decision Conference（CCDC）

作者： Conggui Yuan is with the Automation Department,Guangdong University of Technology,and Mechanical & Electrical Engineering dept,Guangzhou Vocational College of Technology & Business,.XinzhengZhang is with the Automation Department,Guangdong University of Technology.Shuqiong Xu is with the Automation Department,Guangdong University of Technology

An important step in modeling time series is the selection of appropriate model *** theoretic concept of mutual information provides a general framework to evaluate the dependence between a potential model input and the output.A model-free approach,partial measure of the mutual information,is proposed in this paper,which utilizes a measure of the mutual information criterion to characterize the dependence in the case of multiple inputs and identifies the actual inputs for time series *** algorithm is tested on a number of synthetic time series data sets,where the dependence attributes were known a *** depict the effectiveness of the proposed method in proper input selection.

关键词： mutual information Input Selection Time Series

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Visible and Infrared Image Automatic Registration Algorithm Using mutual information

Visible and Infrared Image Automatic Registration Algorithm ...

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2010 Chinese Control and Decision Conference

作者： Jing Jiang~(1,2),Xuesong Zhang~3 1.Electromechanical Engineering Department,North China Institute of Science and Technology,Yanjiao Beijing-East,101601 2.School of Mechanical Electronic & information Engineering,China University of Mining Technology(Beijing),Beijing,100083 3.National Laboratory of Electro-Optics System Technology,Sanhe Hebei,065201

＜正＞In this paper,we introduce a novel visible/infrared image registration algorithm based on wavelet transform and the maximization of mutual information of ***,the region of interest（ROI） is determined by searching for the wavelet magnitude maxima in the preprocessing step,and the affine transform is chosen as the image geometrical transform ***,the probability density function of grey values is estimated from histogram by means of the Partial Volume（PV） interpolation ***,the simulated annealing algorithm is used to approximate the global *** experimental results show that the algorithm is efficient.

关键词： Image registration Visible-Infrared image mutual information Wavelet transform

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The Contribution of mutual information in the Intonational Phrase Prediction In Chinese Text

The Contribution of Mutual Information in the Intonational P...

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2003 International Conference on Natural Language Processing and Knowledge Engineering

作者： Guo-Ping HU Ben-Feng CHEN Ming FAN Ren-Hua WANG University of Science and Technology of China

ISBN: (纸本)0780379020

The contribution of mutual information(MI) in the Intonational Phrase(IP) prediction is analyzed and verified in this *** basic idea of employing MI in IP prediction is that people is likely to pause between the less correlated words,where the MI value is *** paper presents a decision tree based predictor which adopts POS as the main feature firstly as the baseline,and then the paper analyzes the correlation between MI and *** approach which only bases on the MI to predict the IP boundary is demonstrated in this paper,and three methods combining the MI and POS in the predictor is presented *** the MI based approach,a considerable performance(F-Score:64.2%) is achieved,and 3.4% promotion from the baseline is achieved after combining MI and POS in our *** our work indicates that MI is an effective feature in the prosodic phrase boundaries prediction in Chinese text, and combining the MI and POS in the predictor is valuable.

关键词： Intonational Phrase mutual information Prosody Boundary Part-Of-Speech

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Reverse Engineering Gene Regulatory Networks Based on Dynamic Threshold Condition mutual information With Resampling Strategy

Reverse Engineering Gene Regulatory Networks Based on Dynami...

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第40届中国控制会议

作者： Jie Xu Guanxue Yang Guohai Liu Guanxiao Yang School of Electrical and information Engineering Jiangsu University

Recently, constructing relatively accurate gene regulatory networks has become a hot research direction in the field of bioinformatics. Path consistency algorithm based on conditional mutual information（PCACMI） is a practical algorithm to reconstruct gene regulation networks, but the threshold is fixed, which will affect the accuracy of the reconstructed networks. So we improve PCACMI and design a new algorithm termed dynamic threshold condition mutual information（DTCMI）. In the new algorithm, the threshold is related to the maximal element of the weight matrix of different orders, and the value of threshold will change with maximal weights. In addition, in order to improve the accuracy of the reconstructed network, we firstly employ resampling strategy by utilizing the jackknife to deal with the gene expression data. Finally, we reconstruct the networks by using gene knock-out expression data from the stochastic differential equation and DREAM4 challenges. The results show that the performance of DTCMI is more effective.

关键词： Gene regulatory networks mutual information Jackknife Network inference

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Novel Approach to Pavement Cracking Detection Based on Morphology and mutual information

Novel Approach to Pavement Cracking Detection Based on Morph...

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2010 Chinese Control and Decision Conference

作者： LI Gang~1,JU Yongfeng~1 1.School of Electronic and Control Engineering,Chang''an University,Xi''an,710064

＜正＞The image processing technology has been widely applied to pavement cracking detection,but it is difficult to make a balance between the processing effect and *** order to solve this problem,the multi-direction structuring elements morphology and mutual information algorithm for the pavement crack detection is introduced and a novel image processing method is proposed in this *** approached method combines the multi-direction structuring elements morphology with mutual information to segment the crack and the *** the above processing,the proposed method employs the improved contour tracking algorithm to mark the cracks and obtain the contours,and then gets the length and width of cracks by *** with other traditional methods,the experimental results indicate that our method can not only effectively extract the edges of cracks and evidently decrease the influence of noises,but also gain the exact characteristics of the pavement ***,it can provide good image processing speed.

关键词： image segmentation threshold value multi-direction structuring elements mutual information contour tracking

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Analysis Method of Multi-scale Frequency Spectral Latent Feature based on the mutual information

Analysis Method of Multi-scale Frequency Spectral Latent Fea...

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2015 3rd International Conference on Machinery,Materials and information Technology Applications(ICMMITA 2015)

作者： Zhuo Liu Jian Tang Meiying Jia Xiaojie Zhou State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Research Institute of Computing Technology Beifang Jiaotong University

Heavy rotating mechanical devices, such as ball mills in the mineral grinding process, produce strong mechanical vibration and acoustic signals. These signals consist of multiple components with different time scales and physical interpretations. Frequency spectra of these multi-scale sub-signals contain interesting information related to some difficulty-to-measure process parameters. Latent feature extraction methods based on principal component analysis and partial least squares with their kernel versions are used widely for high dimensional spectra data. How to estimate their effect and select important sub-signals are important issues. Thus, aim to these problems, mutual information is used in this paper. Analysis results based on the shell vibration frequency spectra of a laboratory-scale wet ball mill shows that the proposed method is helpful and effective.

关键词： Multi-scale Frequency Spectra Latent Features extraction mutual information

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The mutual information Between a Female Genotypes and its Descendant Genotypes in Mating of Whole Homologous Phenotypes

The Mutual Information Between a Female Genotypes and its De...

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2010 Chinese Control and Decision Conference

作者： Hongyan Zhang~1,Xiaojing Zhou~2,Dong He~2,Dongyan Dai~2,Hongli Zhang~2 1 College of Life Science & Technology,Heilongjiang Bayi Agricultural University,Daqing,163319,China 2 Math Department,Heilongjiang Bayi Agricultural University,Daqing 163319,China

＜正＞The paper studied some questions about a population that was always forced a mating of whole homologous phenotypes at the beginning of a Hardy-Weinberg equilibrium *** joint probability distribution between a female genotypes and its descendant genotypes was deduced on the population;its descendant genotypic conditional entropy gradually reduced when a female genotypes could be known;the mutual information between a female genotypes and its descendant genotypes would gradually reduce after enough generations and tend to be a definite vaule -plnp-qlnq, and the population could reach a non-equilibrium steady state out of Hardy-Weinberg equilibrium *** mathematical simulation results illustrated the correctness of the obtained conclusions.

关键词： Homologous phenotypes Conditional entropy mutual information

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A method based on mutual information and gradient information for medical image registration

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Journal of Southeast University(English Edition) 2003年第1期19卷 35-39页

作者：陈晓燕辜嘉李松毅舒华忠罗立民东南大学生物科学与医学工程系南京210096

mutual information is widely used in medical image registration, because it does not require preprocessing the image. However, the local maximum problem in the registration is insurmountable. We combine mutual information and gradient information to solve this problem and apply it to the non-rigid deformation image registration. To improve the accuracy, we provide some implemental issues, for example, the Powell searching algorithm, gray interpolation and consideration of outlier points. The experimental results show the accuracy of the method and the feasibility in non-rigid medical image registration.

关键词： medical image registration gradient information mutual information multi-modal images non-rigid deformation

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Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

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Chinese Physics B 2024年第8期33卷 579-586页

作者：江嘉杰罗春雄刘峰 The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of PhysicsPeking UniversityBeijing 100871China Center for Quantitative Biology Peking UniversityBeijing 100871China Wenzhou Institute University of Chinese Academy of Sciences Wenzhou 325001China Key Laboratory of Hebei Province for Molecular Biophysics Institute of BiophysicsSchool of Health Science&Biomedical EngineeringHebei University of TechnologyTianjin 300130China

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular ***,it is still unclear how such information is affected by the physically dissipative diffusion *** we study one-dimensional patterning systems with analytical derivation and numerical *** find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration ***,there exists an optimal diffusion constant that maximizes the positional ***,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

关键词： pattern formation positional information mutual information diffusion

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