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The Renyi entropy is an important measure of the information, it is proposedby Renyi in the context of entropy theory as a generalization of Shannonentropy. We study in detail this measure of multivariate autoregressive movingaverage (ARMA) control systems. The characteristic function of output processis represented from the terms of its residual characteristic functions. Simpleexpression to compute the Renyi entropy for the output process of these systemsis derived. In addition, we investigate the covariance matrix for finding theupper bound of the entropy. Finally, we present three separate examples thatserve to illustrate the behavior of information in a multivariate ARMA controlsystem where the control and noise distributed as Gaussian, Cauchy and Laplaceprocesses.

Renyi Entropy of Multivariate Autoregressive Moving Average Control Systems