Method of Local Restoration of Segments of Information Signals

Abstract

The use of centralized and decentralized electricity supply schemes, the introduction of feedback between the consumer of electricity and its producer led to a rapid increase in information flows at all stages of the functioning of the electricity industry of Ukraine, starting with the production of electricity and before its consumption. This necessitates the processing, storage and transmission of large data sets. On the other hand, the time constraints imposed on information processing and decision-making efficiency, as well as the limited bandwidth of communication networks require effective optimization of information flows in terms of their compression and compact storage, transmission and recovery without loss. At the same time, the determining quantitative and qualitative information parameters are electricity consumption modes and the quality of electric energy, and the main mode parameter for solving many problems of planning, management and carrying out commercial calculations is the graphs of electric load. Based on the analysis of the functional relationships of wavelet coefficients according to the levels of wavelet decomposition, the robot presents a modified reconstruction scheme and developed a model based on which a method of local (segmental) restoration of information signals according to the levels of wavelet detail is synthesized using the example of the electric load graph. In the paper, a model of local recovery of time segments of information signals is proposed and a sequential algorithm of actions synthesized on its basis. This technique allows for effective segmentation of information signals, reduces the duration of mathematical processing, simplifies database analysis, increases the effectiveness of controlling the reliability of initial data recovery by reserving recovery paths with subsequent comparison of results.