Neural network formalization of the hungarian party-state system

Abstract

A description of the decision-making structure of the Hungarian Party-state system, based on empirical studies, is offered. The structure is divided into three parts: the formal hierarchies, the interlinking threads, and the feedback connections. The working mechanism, the sources of cohesion, and the maintenance of the system are explained. The working mechanism of the structure reveals pattern-recognition-type decision making and close similarity to the adaptive resonance theory (ART) of competitive learning. The observed analogy is followed throughout the structure. Based on the ART model, we offer a mathematical description of the properties of the structure that could, in principle, be quantified if the model parameters were to be determined by further empirical studies. Properties of the structure are qualitatively analyzed with the help of this mathematical model. The self-similar or fractal property of the structure makes it possible to analyze some features of other Party-state systems.