Title :
Real time CCD-based neural network system for pattern recognition applications
Author :
Chiang, Alice M.
Author_Institution :
Lincoln Lab., MIT, Lexington, MA, USA
fDate :
31 Aug-2 Sep 1992
Abstract :
A generic NNC (neural network classifier) capable of providing 1.9 billion programmable connections per second is described. Applications for these generic processors include image and speech recognition as well as sonar signal identification. To demonstrate the modularity and flexibility of the CCD (charge coupled device) NNCs, two generic multilayer system-level boards capable of both feedforward and feedback nets are presented. The boards demonstrate multiple LL NN chips in an adaptable, reconfigurable, expandable multipurpose system design. Although only two examples are demonstrated, the extension to larger and more complicated networks using multiple NN devices as building blocks is straightforward
Keywords :
CCD image sensors; charge-coupled device circuits; feedforward neural nets; image recognition; neural chips; real-time systems; recurrent neural nets; signal detection; speech recognition; feedback nets; flexibility; generic NNC; image recognition; modularity; multilayer system-level boards; neural network classifier; pattern recognition; radar signal identification; real time CCD-based neural network system; sonar signal identification; speech recognition; Buffer storage; Charge coupled devices; Computer architecture; Concurrent computing; Electronic mail; Laboratories; Neural networks; Neurons; Pattern recognition; Real time systems;
Conference_Titel :
Neural Networks for Signal Processing [1992] II., Proceedings of the 1992 IEEE-SP Workshop
Conference_Location :
Helsingoer
Print_ISBN :
0-7803-0557-4
DOI :
10.1109/NNSP.1992.253651