Title :
RA: an analog neurocomputer for the synchronous Boltzmann machine
Author :
Pujol, H. ; Klein, J.O. ; Belhaire, E. ; Garda, P.
Author_Institution :
Inst. d´´Electron. Fondamentale, Univ. de Paris-Sud, Orsay, France
Abstract :
The Random Analog (RA) Neurocomputer runs synchronous Boltzmann machines dedicated to real time visual pattern recognition. Its architecture achieves scalability and modularity thanks to a linear array of analog processing modules linked by a high bandwidth interconnection network, a controller, and a front end running a high level user interface. A prototype with 128 input neurons and 64 active neurons and 4.2 GCPS peak processing power is described and simulation results are given
Keywords :
Boltzmann machines; Random Analog Neurocomputer; analog processing modules; high level user interface; linear array; modularity; real time visual pattern recognition; scalability; synchronous Boltzmann machine; Bandwidth; CMOS technology; Computer architecture; Image processing; Multiprocessor interconnection networks; Neural networks; Neurons; Prototypes; Scalability; Temperature;
Conference_Titel :
Microelectronics for Neural Networks and Fuzzy Systems, 1994., Proceedings of the Fourth International Conference on
Conference_Location :
Turin
Print_ISBN :
0-8186-6710-9
DOI :
10.1109/ICMNN.1994.593741
