Algorithms for Continuous Compression of Measurement Data Frames within the Spatial Approach
Ilya Bogachev, Alexey Viktorovitch Levenets, En Un Chye, Mark Sharapov · 2023
Statement of the problem: for telemetry systems, among the variety of problems, we can distinguish a special class of problems related to the development of algorithms for continuous data processing. Their allocation into a separate class is due to the fact that within the framework of both the classical approach to compression and the spatial approach, this problem was considered strictly discretely, without taking into account deep correlations both in time between samples of the same source and between samples obtained in one point in time from different sources. Purpose of the study: development of effective adaptive and non-adaptive algorithms for continuous compression of measurement data frames. Results: algorithms for continuous compression of measurement data frames have been developed. A comparative analysis of the efficiency of their work and the work of a discrete compression algorithm based on the construction of prefix Huffman codes was carried out, which showed their significant superiority over this algorithm either in the compression ratio (adaptive algorithm) or in its speed (non-adaptive algorithm).