DocumentCode
1579978
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
fYear
1992
Firstpage
820
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neuroinformatics and Neurocomputers, 1992., RNNS/IEEE Symposium on
Conference_Location
Rostov-on-Don
Print_ISBN
0-7803-0809-3
Type
conf
DOI
10.1109/RNNS.1992.268636
Filename
268636
Link To Document