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Exact(48)
First, we give the gradient of mutual information with respect to precoding matrix B. To start with, we give the gradient of mutual information with respect to the linear precoding matrix B, which was initially proposed in [17].
Each component carries information from the entire data cube, and is likely to represent some pattern that shares little mutual information with the other components.
We use the difference between the extrinsic mutual information with full and no prior information input as measurement to characterize a specific mapping.
Both algorithms are based on mutual information with the main difference being the number of samples used for the similarity function (for example, the slow algorithm is supposed to be more accurate but is more time-consuming).
In [37], Kraskov et al. reported on a modified KL estimator to compute mutual information with improved performance and applicability in higher dimensional spaces (the result is referred to as the KSG algorithm).
It can be observed that the mutual information with the precoding design to maximize the mutual information is better than that of the precoding design to minimize the soft detection error.
Similar(11)
All the mutual information associated with the other features decrease along with the reducing sampling rate.
The solution is derived from a maximum mutual information argument with a single transmitter.
We performed a mutual information calculation with a sum of the previous ISIs, successively adding more times.
Therefore, combining mutual information analysis with robust clustering of complex stimuli provides a framework to study neural coding mechanisms related to complex stimuli discrimination.
Each component of the decomposition is a mutual information measure with respect to a single input, conditioned on a subset of the remaining inputs.
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Justyna Jupowicz-Kozak
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