Implementation of probabilistic automata in weightless neural networks

摘要

The objective of this paper is to analyze the practical viability of the results theoretical concerning the relationship of a class of weightless neural networks, known as General Single-layer Sequential Weightless Neural Networks (GSSWNNs), and Probabilistic Automata (PA). This study was based on the theoretical model development by de Souto [1]. This model shows the computational equivalence between the GSSWNNs and the PAs. However, in order to develop a practical implementation, it is important to explain questionings concerning the need, or not, to make restrictions on the original theoretical results.