Neural networks processing systems in recognition and control problems

Abstract

The construction principles and architecture of neural network processing systems (NPSs) are considered. Attention is given to mechatronic system adaptation using NPS-based control, an NPS-based robot adaptive control architecture, threshold-polynomial training algorithms for recognition, and probabilistic training algorithms of logical NPSs for recognition. >