Abstract
This article presents the implementation of a modified parallel-pyramidal algorithm for the efficient processing and identification of images. The method involves creating a systemic model that supports spatial, temporal, and network data integration, forming a dynamic pyramidal-hierarchical network. The article details the techniques for sorting vectors, G-transformations for modifying vector elements, and the shifting procedure that facilitates efficient data transformation. The described procedures are integrated into the overall data processing sequence, which includes the iterative application of these methods until the final result is achieved.