Metrics for matrix-valued measures via test functions

TL;DR

The paper introduces a new weakly-continuous metric for comparing matrix-valued measures, especially power spectral densities, extending the dual interpretation of measure distances to matrix-valued functions.

Contribution

It develops a novel Wasserstein-like metric for matrix-valued densities using test functions, enhancing tools for spectral analysis.

Findings

The new metric is weakly continuous and suitable for matrix-valued spectral densities.

Comparison with existing metrics shows advantages in certain applications.

Numerical examples demonstrate the effectiveness of the proposed metric.

Abstract

It is perhaps not widely recognized that certain common notions of distance between probability measures have an alternative dual interpretation which compares corresponding functionals against suitable families of test functions. This dual viewpoint extends in a straightforward manner to suggest metrics between matrix-valued measures. Our main interest has been in developing weakly-continuous metrics that are suitable for comparing matrix-valued power spectral density functions. To this end, and following the suggested recipe of utilizing suitable families of test functions, we develop a weakly-continuous metric that is analogous to the Wasserstein metric and applies to matrix-valued densities. We use a numerical example to compare this metric to certain standard alternatives including a different version of a matricial Wasserstein metric developed earlier.