This article examines the structures of one of the types of pyramidal networks - parallel-hierarchical networks. The presented material has a dual purpose - applied and cognitive. The first one is of great importance in increasing the "intelligence" of specialized computer tools using a bionic approach. The second one opens completely new possibilities for a deeper understanding of the structure of the brain from the perspective of the cybernetic approach.
This paper describes an approach to solving the problem of fast pattern recognition with image co-ordinate detection and measurement under undefined noise and signal conditions. An analysis of the use of the W-transform method as a basis for image comparison algorithms was carried out. Image comparison algorithms with noise robustness were developed.
The article examines the analysis of the multistage process of correlation interactions in parallel-hierarchical structures for organization of neuro-like calculations. The process of formation of parallel-hierarchical network is considered in detail. The graph-scheme of PH transformation is given. The process of elements formation for five levels of the network is analyzed. It was determined which elements are correlated and decorrelated in time. Based on the analysis, a structural-functional model of correlation interactions of parallel-hierarchical network elements was developed.
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