Quantifying Similarity and Distance Measures for Vector-Based Datasets: Histograms, Signals, and Probability Distribution Functions

Report No. ARL-TN-0810
Authors: by Mark A Tschopp and Efraín Hernández–Rivera
Date/Pages: February 2017; 40 pages
Abstract: It is often important to characterize the similarity or dissimilarity (distance) between different measured or computed datasets. There are a large number of different possible similarity and distance measures that can be applied to different datasets. In this technical note, a number of different measures implemented in both MATLAB and Python as functions are used to quantify similarity/distance between 2 vector-based datasets. The scripts are attached as appendixes as is a description of their execution.
Distribution: Approved for public release
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Last Update / Reviewed: February 1, 2017