scholarly journals Transfer entropy and cumulant based cost as measures of nonlinear causal relationships in space plasmas: applications to <i>D<sub><i>st</i></i>

2018 ◽  
Author(s):  
Jay R. Johnson ◽  
Simon Wing ◽  
Enrico Camporeale
Keyword(s):  
Solar Wind ◽  
Mutual Information ◽  
Strong Correlation ◽  
Information Transfer ◽  
Ring Current ◽  
Space Physics ◽  
Transfer Entropy ◽  
Linear Relationships ◽  
Transfer Of Information

Abstract. It is well known that the magnetospheric response to the solar wind is nonlinear. Information theoretical tools such as mutual information, transfer entropy, and cumulant based analysis are able to characterize the nonlinearities in the system. Using cumulant based cost, we show that nonlinear significance of Dst peaks at 3–12 hours lags that can be attributed to VBs which also exhibit similar behavior. However, the nonlinear significance that peaks at lags 25, 50, and 90 hours can be attributed to internal dynamics, which may be related to the relaxation of the ring current. These peaks are absent in the linear and nonlinear self-significance of VBs. Our analysis with mutual information and transfer entropy show that both methods can establish that there are a strong correlation and transfer of information from Vsw to Dst at a time scale that is consistent with that obtained from the cumulant based analysis. However, mutual information also shows that there is a strong correlation in the backward direction, from Dst to Vsw, which is counterintuitive. In contrast, transfer entropy shows that there is no or little transfer of information from Dst to Vsw, as expected because it is the solar wind that drives the magnetosphere, not the other way around. Our case study demonstrates that these information theoretical tools are quite useful for space physics studies because these tools can uncover nonlinear dynamics that cannot be seen with the traditional analyses and models that assume linear relationships.

scholarly journals Transfer entropy and cumulant-based cost as measures of nonlinear causal relationships in space plasmas: applications to <i>D</i><sub>st</sub>

2018 ◽  
Vol 36 (4) ◽  
pp. 945-952 ◽  
Author(s):  
Jay R. Johnson ◽  
Simon Wing ◽  
Enrico Camporeale
Keyword(s):  
Solar Wind ◽  
Mutual Information ◽  
Information Transfer ◽  
Ring Current ◽  
Space Physics ◽  
Transfer Entropy ◽  
Strong Correlations ◽  
Linear Relationships ◽  
Transfer Of Information

Abstract. It is well known that the magnetospheric response to the solar wind is nonlinear. Information theoretical tools such as mutual information, transfer entropy, and cumulant-based analysis are able to characterize the nonlinearities in the system. Using cumulant-based cost, we show that nonlinear significance of Dst peaks at 3–12 h lags that can be attributed to VBs, which also exhibits similar behavior. However, the nonlinear significance that peaks at lags 25, 50, and 90 h can be attributed to internal dynamics, which may be related to the relaxation of the ring current. These peaks are absent in the linear and nonlinear self-significance of VBs. Our analysis with mutual information and transfer entropy shows that both methods can establish that there are strong correlations and transfer of information from Vsw to Dst at a timescale that is consistent with that obtained from the cumulant-based analysis. However, mutual information also shows that there is a strong correlation in the backward direction, from Dst to Vsw, which is counterintuitive. In contrast, transfer entropy shows that there is no or little transfer of information from Dst to Vsw, as expected because it is the solar wind that drives the magnetosphere, not the other way around. Our case study demonstrates that these information theoretical tools are quite useful for space physics studies because these tools can uncover nonlinear dynamics that cannot be seen with the traditional analyses and models that assume linear relationships.

EEG TRANSFER ENTROPY TRACKS CHANGES IN INFORMATION TRANSFER ON THE ONSET OF VISION

2012 ◽  
Vol 17 ◽  
pp. 9-18 ◽  
Author(s):  
M. D. MADULARA ◽  
P. A. B. FRANCISCO ◽  
S. NAWANG ◽  
D. C. AROGANCIA ◽  
C. J. CELLUCCI ◽  
...  
Keyword(s):  
Mutual Information ◽  
Information Transfer ◽  
Occipital Lobe ◽  
Transfer Entropy ◽  
The Other ◽  
Information Measures ◽  
Eyes Closed ◽  
Eyes Open ◽  
Almost All ◽  
Nonlinear Correlations

We investigate the pairwise mutual information and transfer entropy of ten-channel, free-running electroencephalographs measured from thirteen subjects under two behavioral conditions: eyes open resting and eyes closed resting. Mutual information measures nonlinear correlations; transfer entropy determines the directionality of information transfer. For all channel pairs, mutual information is generally lower with eyes open compared to eyes closed indicating that EEG signals at different scalp sites become more dissimilar as the visual system is engaged. On the other hand, transfer entropy increases on average by almost two-fold when the eyes are opened. The largest one-way transfer entropies are to and from the Oz site consistent with the involvement of the occipital lobe in vision. The largest net transfer entropies are from F3 and F4 to almost all the other scalp sites.

scholarly journals Information Transfer between Generations Linked to Biodiversity in Rock-Paper-Scissors Games

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ranjan Bose
Keyword(s):  
Mutual Information ◽  
Information Transfer ◽  
Communication Channel ◽  
Channel Model ◽  
Ecological Processes ◽  
Interacting Species ◽  
Generalized Framework ◽  
Unequal Rates ◽  
Successive Generations ◽  
Transfer Of Information

Ecological processes, such as reproduction, mobility, and interaction between species, play important roles in the maintenance of biodiversity. Classically, the cyclic dominance of species has been modelled using the nonhierarchical interactions among competing species, represented by the “Rock-Paper-Scissors” (RPS) game. Here we propose a cascaded channel model for analyzing the existence of biodiversity in the RPS game. The transition between successive generations is modelled as communication of information over a noisy communication channel. The rate of transfer of information over successive generations is studied using mutual information and it is found that “greedy” information transfer between successive generations may lead to conditions for extinction. This generalized framework can be used to study biodiversity in any number of interacting species, ecosystems with unequal rates for different species, and also competitive networks.

scholarly journals Causality and Information Transfer Between the Solar Wind and the Magnetosphere–Ionosphere System

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 390
Author(s):  
Pouya Manshour ◽  
Georgios Balasis ◽  
Giuseppe Consolini ◽  
Constantinos Papadimitriou ◽  
Milan Paluš
Keyword(s):  
Solar Wind ◽  
Information Transfer ◽  
Linear Time ◽  
Vertical Component ◽  
Causal Link ◽  
Theoretic Approach ◽  
Geomagnetic Disturbances ◽  
Magnetospheric Substorms ◽  
Solar Wind Parameters ◽  
Information Theoretic Approach

An information-theoretic approach for detecting causality and information transfer is used to identify interactions of solar activity and interplanetary medium conditions with the Earth’s magnetosphere–ionosphere systems. A causal information transfer from the solar wind parameters to geomagnetic indices is detected. The vertical component of the interplanetary magnetic field (Bz) influences the auroral electrojet (AE) index with an information transfer delay of 10 min and the geomagnetic disturbances at mid-latitudes measured by the symmetric field in the H component (SYM-H) index with a delay of about 30 min. Using a properly conditioned causality measure, no causal link between AE and SYM-H, or between magnetospheric substorms and magnetic storms can be detected. The observed causal relations can be described as linear time-delayed information transfer.

scholarly journals Prediction of SYM-H index during large storms by NARX neural network from IMF and solar wind data

2010 ◽  
Vol 28 (2) ◽  
pp. 381-393 ◽  
Author(s):  
L. Cai ◽  
S. Y. Ma ◽  
Y. L. Zhou
Keyword(s):  
Neural Network ◽  
Solar Wind ◽  
Correlation Coefficient ◽  
Characteristic Time ◽  
Ring Current ◽  
Wind Data ◽  
Distinct Advantage ◽  
Elman Network ◽  
H Index ◽  
Narx Neural Network

Abstract. Similar to the Dst index, the SYM-H index may also serve as an indicator of magnetic storm intensity, but having distinct advantage of higher time-resolution. In this study the NARX neural network has been used for the first time to predict SYM-H index from solar wind (SW) and IMF parameters. In total 73 time intervals of great storm events with IMF/SW data available from ACE satellite during 1998 to 2006 are used to establish the ANN model. Out of them, 67 are used to train the network and the other 6 samples for test. Additionally, the NARX prediction model is also validated using IMF/SW data from WIND satellite for 7 great storms during 1995–1997 and 2005, as well as for the July 2000 Bastille day storm and November 2001 superstorm using Geotail and OMNI data at 1 AU, respectively. Five interplanetary parameters of IMF Bz, By and total B components along with proton density and velocity of solar wind are used as the original external inputs of the neural network to predict the SYM-H index about one hour ahead. For the 6 test storms registered by ACE including two super-storms of min. SYM-H<−200 nT, the correlation coefficient between observed and NARX network predicted SYM-H is 0.95 as a whole, even as high as 0.95 and 0.98 with average relative variance of 13.2% and 7.4%, respectively, for the two super-storms. The prediction for the 7 storms with WIND data is also satisfactory, showing averaged correlation coefficient about 0.91 and RMSE of 14.2 nT. The newly developed NARX model shows much better capability than Elman network for SYM-H prediction, which can partly be attributed to a key feedback to the input layer from the output neuron with a suitable length (about 120 min). This feedback means that nearly real information of the ring current status is effectively directed to take part in the prediction of SYM-H index by ANN. The proper history length of the output-feedback may mainly reflect on average the characteristic time of ring current decay which involves various decay mechanisms with ion lifetimes from tens of minutes to tens of hours. The Elman network makes feedback from hidden layer to input only one step, which is of 5 min for SYM-H index in this work and thus insufficient to catch the characteristic time length.

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