Title :
An analog continuous-time programmable neural network
Author :
Khachab, Nabil I. ; Ismail, Mohammed
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
The authors introduce economical, simple, and versatile MOS cells that achieve vector scalar product and are applicable in the MOS implementation of feedback/feedforward neural networks. The vector scalar product of 2 n-tuple vector inputs is achieved by using 2(n+1) MOS transistors, thus offering an economical alternative to VLSI analog neural networks. The analog neural network is realized by interconnecting double inverters to the new vector scalar product circuits. The output voltage is tunable programmable DC control voltages. Experimental results are presented
Keywords :
MOS integrated circuits; analogue processing circuits; neural chips; voltage control; MOS cells; MOS transistors; analog continuous-time programmable neural network; feedback/feedforward neural networks; inverters; n-tuple vector inputs; programmable DC control voltages; vector scalar product; Biological neural networks; Circuit simulation; Integrated circuit interconnections; MOSFETs; Neural networks; Neurofeedback; Power generation economics; Resistors; Threshold voltage; Voltage control;
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.1992.268559