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Analyzing information transfer in time-varying multivariate data

Chaoli Wang, Hongfeng Yu, Ray W. Grout, Kwan-Liu Ma, Jacqueline H. Chen
2011 2011 IEEE Pacific Visualization Symposium  
In this paper, we present a new approach to analyzing and visualizing timevarying multivariate volumetric and particle data sets through the study of information flow using the information-theoretic concept  ...  We demonstrate this information-theoretic approach and present our findings with three time-varying multivariate data sets produced from scientific simulations.  ...  We utilize transfer entropy to analyze and visualize information flow in scientific data sets.  ... 
doi:10.1109/pacificvis.2011.5742378 dblp:conf/apvis/WangYGMC11 fatcat:3t6vlwrvbzakdjbtqnrzzi424i

Multivariate spatial data visualization: a survey

Xiangyang He, Yubo Tao, Qirui Wang, Hai Lin
2019 Journal of Visualization  
Multivariate spatial data plays an important role in computational science and engineering simulations.  ...  We first introduce the basic concept and characteristics of multivariate spatial data, and describe three main tasks in multivariate data visualization: feature classification, fusion visualization, and  ...  In addition, the correlation between multiple time steps in time-varying multivariate data needs to be examined.  ... 
doi:10.1007/s12650-019-00584-3 fatcat:2evmvj76wjhvxe4gfrusvvggpm

A Tri-Space Visualization Interface for Analyzing Time-Varying Multivariate Volume Data [article]

Hiroshi Akiba, Kwan-Liu Ma
2007 EUROVIS 2005: Eurographics / IEEE VGTC Symposium on Visualization  
The three components are tightly linked to facilitate tri-space data exploration, which offers scientists new power to study their time-varying, multivariate volume data.  ...  In order to analyze and understand such data, scientists need the capability to explore simultaneously in the temporal, spatial, and variable domains of the data.  ...  Acknowledgments This research was supported in part by the U.S.  ... 
doi:10.2312/vissym/eurovis07/115-122 fatcat:hfgzbtuvwveoloogr3ax37v2xu

Reconstructing complex network for characterizing the time-varying causality evolution behavior of multivariate time series

Meihui Jiang, Xiangyun Gao, Haizhong An, Huajiao Li, Bowen Sun
2017 Scientific Reports  
In order to explore the characteristics of the evolution behavior of the time-varying relationships between multivariate time series, this paper proposes an algorithm to transfer this evolution process  ...  The approach presents a potential to analyze multivariate time series and provides important information for investors and decision makers.  ...  The process of building the multivariate time-varying causality transition network is shown in Fig. 2 . Sample data. In this paper, we focus on the relationships between multivariate time series.  ... 
doi:10.1038/s41598-017-10759-3 pmid:28874713 pmcid:PMC5585247 fatcat:p6a72dexwrcbvjkfmgunvyb4tm

Directed information measures for assessing perceived audio quality using EEG

Ketan Mehta, Jorg Kliewer
2015 2015 49th Asilomar Conference on Signals, Systems and Computers  
We exploit directed information to examine the causal relationship between EEG data in response to audio stimulus.  ...  Different types of directed information measures are then used to quantify the information flow between EEG sensors, which are grouped into different regions of interest over the cortex.  ...  Specifically, there has been a growing interest in using DI measures to analyze EEG data.  ... 
doi:10.1109/acssc.2015.7421096 dblp:conf/acssc/MehtaK15 fatcat:s7dujudkgzebtgr7gimtatghp4

Comparison of linear signal processing techniques to infer directed interactions in multivariate neural systems

Matthias Winterhalder, Björn Schelter, Wolfram Hesse, Karin Schwab, Lutz Leistritz, Daniel Klan, Reinhard Bauer, Jens Timmer, Herbert Witte
2005 Signal Processing  
The information contained in electromagnetic signals may be used to quantify the information transfer between those structures.  ...  In an application to neural data recorded by electrothalamography and electrocorticography from juvenile pigs under sedation, directed as well as time-varying interactions have been studied between thalamic  ...  Fifth, time-varying dynamic effects are analyzed to investigate their performance on non-stationary data.  ... 
doi:10.1016/j.sigpro.2005.07.011 fatcat:r2pihmujnvekvoofe2le5hizqe

Brain Mapping using Compressed Sensing with Graphical Connectivity Maps

S. Archana, K. A. Narayanankutty, Anand Kumar
2012 International Journal of Computer Applications  
Utility of graphical representation of EEG data and colourmaps are now well established. Research on localisation and activity in neuronal pathway are also progressing.  ...  In this paper, the same is constructed using a compressed sensing technique. A GUI with the connected graph and magnitudes are also generated from EEG.  ...  Besides, connectivity using adaptive directed transfer function, which determine the timevariant connectivity pattern by analyzing time-varying coefficients obtained from a multivariate adaptive autoregressive  ... 
doi:10.5120/8614-2474 fatcat:myhs3puy3fdcpicdargcy4dso4

voxel2vec: A Natural Language Processing Approach to Learning Distributed Representations for Scientific Data [article]

Xiangyang He and Yubo Tao and Shuoliu Yang and Haoran Dai and and Hai Lin
2022 arXiv   pre-print
for multivariate data and to association analysis for time-varying and ensemble data.  ...  of volumes in time-varying and ensemble data, are intricate and complex.  ...  Time-varying Data We use transfer prediction to analyze the association between volumes in the ABC-flow data set in Eq. 8.  ... 
arXiv:2207.02565v2 fatcat:mv2q3pfiyvhabgsmvf6splwuvu

Characterizing Multivariate Information Flows [article]

Shohei Hidaka
2012 arXiv   pre-print
The proposed measure, called multivariate transfer entropy, is an extension of transfer entropy, a measure of temporal predictability.  ...  The present study proposes a new information-theoretic measure with consideration to such potential multivariate relationships.  ...  This work was supported by Artificial Intelligence Research Promotion Foundation and Grant-in-Aid for Scientific Research B No. 23300099.  ... 
arXiv:1212.5449v1 fatcat:jsb4zfglxrflfajmgkpiutokzu

Information and Knowledge assisted analysis and Visualization of large-scale data

Chaoli Wang, Kwan-Liu Ma
2008 2008 Workshop on Ultrascale Visualization  
As a result, in recent years, we have seen increasing research and development efforts into the area of Information and Knowledge assisted Visualization (IKV).  ...  In this paper, we survey research in IKV of scientific data and also identify a few directions for further work in this emerging area.  ...  ACKNOWLEDGMENT This work was supported in part by the U.S.  ... 
doi:10.1109/ultravis.2008.5154057 fatcat:ezo5zxlpsnhmbgj74nzrwdpwam

Accurate information transmission through dynamic biochemical signaling networks

J. Selimkhanov, B. Taylor, J. Yao, A. Pilko, J. Albeck, A. Hoffmann, L. Tsimring, R. Wollman
2014 Science  
(A) Overview of single-cell data analyzed in this work. (B) Examples of single-cell response dynamic trajectories.  ...  IER was estimated in two ways: by (i) quantifying the fluctuations in the later (quasistationary) portion of the response time series of our ERK data ( fig.  ...  The super-enhancer encompassing TAL1 in Jurkat cells was aberrant, in that it was not present in fetal thymocytes, normal CD34+ hematopoietic stem and progenitor cells (HSPCs), or in other T-ALL cell lines  ... 
doi:10.1126/science.1254933 pmid:25504722 pmcid:PMC4813785 fatcat:fddwf6v235bubk2zlgwdniu5sq

Dynamic process connectivity explains ecohydrologic responses to rainfall pulses and drought

Allison E. Goodwell, Praveen Kumar, Aaron W. Fellows, Gerald N. Flerchinger
2018 Proceedings of the National Academy of Sciences of the United States of America  
joint asynchronous time dependencies.  ...  We use an information theory-based approach to quantify connectivity in the form of information flow associated with the propagation of fluctuations between variables.  ...  The MATLAB toolbox for computing TIPNet information transfer measures can be downloaded at HydroComplexity/TIPNet.  ... 
doi:10.1073/pnas.1800236115 pmid:30150371 fatcat:tnduqmw36ra5bhr6ve7ffe6mzm

Ambient PMU Data Based System Oscillation Analysis Using Multivariate Empirical Mode Decomposition [article]

Shutang You
2021 arXiv   pre-print
Wide-area synchrophasor ambient measurements provide a valuable data source for real-time oscillation mode monitoring and analysis.  ...  Based on multivariate empirical mode decomposition (MEMD), which can analyze multi-channel non-stationary and nonlinear signals, the proposed method is capable of detecting the common oscillation mode  ...  Due to its data-driven nature and the strong capability in analyzing non-stationary signals to provide information on localized amplitudes and frequencies, EMD has been proved to be effective for time-frequency  ... 
arXiv:2101.05203v2 fatcat:oxcr4xcknnh4noq63blcukxpeq

Page 3874 of Mathematical Reviews Vol. , Issue 96f [page]

1996 Mathematical Reviews  
Control Inform. 11 (1994), no. 4, 277-309. In this paper the authors analyze ihe digital H™ y-suboptimal control for a Pritchard-Salamon system.  ...  This results in a relatively simple method in the transfer function domain.  ... 

Windowed multivariate autoregressive model improving classification of labor vs. pregnancy contractions

Brynjar Karlsson, Mahmoud Hassan, Catherine Marque
2013 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
Í We are also indebted to Mr. sgeir Alexandersson for his help in the acquisition of EHG signals.  ...  Conclusion In this paper, we proposed a time varying version of MVAR model.  ...  Discussion In this paper we have proposed a time varying version of the multivariate autoregressive model to investigate the connectivity between non-stationary signals.  ... 
doi:10.1109/embc.2013.6611279 pmid:24111466 pmcid:PMC3883361 dblp:conf/embc/KarlssonHM13 fatcat:xyi6cesa7jdpzf3mrfunullwmu
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