Analog VLSI and neural systems
Analog VLSI and neural systems
VLSI-Compatible Immplementations for Artificial Neural Networks
VLSI-Compatible Immplementations for Artificial Neural Networks
GLS '98 Proceedings of the Great Lakes Symposium on VLSI '98
Toward a general-purpose analog VLSI neural network with on-chip learning
IEEE Transactions on Neural Networks
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This paper offers a new methodology for designing in CMOS technology analog-digital artificial neurons training on arbitrary logical threshold functions of some number of variables. The problems of functional ability, implementability restrictions, noise stability, and refreshment of the learned state are formulated and solved. Some functional problems in experiments on teaching logical functions to an artificial neuron are considered. Recommendations are given on selecting testing functions and generating teaching sequences. All results in the paper are obtained using SPICE simulation. For simulation experiments with analog/digital CMOS circuits, transistor models MOSIS BSIM3v3.1, 0.8amicro;m, level 7 are used.