An efficient algorithm for the computation of average mutual information: Validation and implementation in Matlab

Average mutual information (AMI) measures the dependence between pairs of random variables. It has been used in many applications including blind source separation, data mining, neural synchronicity assessment, and state space reconstruction in human movement studies. Presently, several algorithms and computational code exist to estimate AMI. However, most are difficult to use and/or understand the manner by which AMI is calculated. We offer a straightforward and implementable function in Matlab (Mathworks, Inc.) for the computation of AMI in relatively modest sized data streams (N