Fisher-Rao distances between finite-energy signals in Gaussian noise

TL;DR

This paper introduces a method to measure the similarity between finite-energy signals in Gaussian noise by representing them as probability distributions and using the Fisher-Rao distance from information geometry.

Contribution

The paper develops a novel approach to quantify signal differences in noisy environments through information-geometric measures, bridging signal processing and statistical geometry.

Findings

Fisher-Rao distance effectively characterizes signal differences in Gaussian noise.

The proposed method provides a geometric interpretation of signal similarity.

Application potential in signal classification and detection.

Abstract

This paper proposes representing finite-energy signals observed within a given bandwidth as parameters of a probability distribution and employing the information-geometric framework to compute the Fisher-Rao distance between these signals, considered as distributions.