Title :
A new continuous-time MOS implementation of feedback neural networks
Author :
Khachab, Nabil I. ; Ismail, Mohammed
Author_Institution :
Solid-State Lab., Ohio State Univ., Columbus, OH, USA
Abstract :
An economical, simple, and versatile MOS cell that lends itself to the MOS implementation of feedback/feedforward neural networks is introduced. The new cell achieves vector scalar product of the form Σ TijVj, where y=1 . . ., n, i is fixed, Vj is the output of neuron i, and Tij is the assigned positive or negative weight that is realized through voltage levels. The new circuit comprises only one operational amplifier (op-amp) and two input MOS depletion transistors. The vector scalar product of 2 n-tuple vector inputs is achieved by using 2(n +1) MOS transistors. This offers an economical alternative for VLSI analog neural networks. The analog neural network is realized by interconnecting double inverters through the new vector scalar product circuits. Moreover, the output voltage is tunable via programmable DC control voltages. The technique is demonstrated with an example of a two neuron circuit
Keywords :
MOS integrated circuits; VLSI; analogue circuits; feedback; neural nets; MOS cell; VLSI analog neural networks; continuous-time; double inverters; feedback neural networks; feedforward neural networks; implementation; input MOS depletion transistors; negative weight; operational amplifier; positive weight; programmable DC control voltages; vector scalar product; Feedforward neural networks; Integrated circuit interconnections; Inverters; MOSFETs; Neural networks; Neurofeedback; Neurons; Operational amplifiers; Very large scale integration; Voltage;
Conference_Titel :
Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on
Conference_Location :
Champaign, IL
DOI :
10.1109/MWSCAS.1989.101833