Abstract
In information geometry a Riemannian manifold of probability distributions is considered with the metric given by Fisher information matrix. In this paper we approach explicit forms for the Fisher-Rao distance in spaces composed by multivariate normal distributions of particular forms. Upper bounds for the distance between two general normal distributions are presented and their tightness are discussed in specific cases.
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