Title :
The Two-Stage Analog Neural Network Model and Hardware Implementation
Author :
Kawaguchi, Masashi ; Umeno, Masayoshi ; Ishii, Naohiro
Author_Institution :
Dept. of Electr. & Electron. Eng., Suzuka Nat. Coll. of Technol., Suzuka, Japan
fDate :
Aug. 31 2014-Sept. 4 2014
Abstract :
In the neural network field, many application models have been proposed. A neuro chip and an artificial retina chip are developed to comprise the neural network model and simulate the biomedical vision system. Previous analog neural network models were composed of the operational amplifier and fixed resistance. It is difficult to change the connection coefficient. In this study, we used analog electronic multiple and sample hold circuits. The connecting weights describe the input voltage. It is easy to change the connection coefficient. This model works only on analog electronic circuits. It can finish the learning process in a very short time and this model will enable more flexible learning.
Keywords :
neural nets; sample and hold circuits; analog electronic circuits; analog electronic multiple circuit; artificial retina chip; biomedical vision system simulation; hardware implementation; learning process; neuro chip; sample hold circuit; two-stage analog neural network model; Biological neural networks; Biological system modeling; Integrated circuit modeling; Joining processes; Neurons; SPICE; Solid modeling; electronic circuit; multiple circuit; neural network;
Conference_Titel :
Advanced Applied Informatics (IIAIAAI), 2014 IIAI 3rd International Conference on
Conference_Location :
Kitakyushu
Print_ISBN :
978-1-4799-4174-2
DOI :
10.1109/IIAI-AAI.2014.184