Visual space-time complexity analysis of big signal data

Abstract

This paper will focus on introducing visual analysis for big signal data suitable for preliminary conclusions and information presented to others. The analysis is to determine uniqueness, focusing on spatial-temporal complexity by the nature of the test data. Alongside introducing the analysis and optimization for programming purposes, the real data will be presented and used to display possible usage of this analysis and to determine the uniqueness of electromagnetic background for the possible use in true random number generators. The data consists of measurements in frequency band increments in many locations using widely available consumer-grade equipment. Visual analyses are especially valuable in situations like search for entropy sources because there is no immediate need for a concrete number or boolean statement of the uniqueness; moreover, presenting work is the daily job of a researcher, and the ability to visualize findings in a simple figure is easier to digest by the wider population.