Title :
Neural networks processing systems in recognition and control problems
Author :
Timopheev, Adil V. ; Prokhorov, Danil V.
Author_Institution :
Inst. of Inf. & Autom., Acad. of Sci., St. Petersburg, Russia
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
Keywords :
adaptive control; learning (artificial intelligence); mechatronics; neural nets; pattern recognition; polynomials; probabilistic logic; robots; construction principles; mechatronic system adaptation; neural network processing systems; probabilistic training algorithms; recognition; robot adaptive control architecture; threshold-polynomial training algorithms; Adaptive control; Automatic control; Automation; Computer networks; Control systems; Informatics; Intelligent networks; Mechatronics; Neural networks; Parallel robots;
Conference_Titel :
Neuroinformatics and Neurocomputers, 1992., RNNS/IEEE Symposium on
Conference_Location :
Rostov-on-Don
Print_ISBN :
0-7803-0809-3
DOI :
10.1109/RNNS.1992.268636
