Mutual information based measures on complex interdependent networks of neuro data sets
We assume that even the simplest model of the brain is nonlinear and ‘causal’. Proceeding with the first assumption, we need a measure that is able to capture nonlinearity and hence Mutual Information whose variants includes Transfer Entropy is chosen. The second assumption of ‘causality’ is defined...
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Imperial College London
2013
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.576003 |