Title :
An analog CMOS chip set for neural networks with arbitrary topologies
Author :
Lansner, John A. ; Lehmann, Torsten
Author_Institution :
Electron. Inst., Tech. Univ. of Denmark, Lyngby, Denmark
fDate :
5/1/1993 12:00:00 AM
Abstract :
An analog CMOS chip set for implementations of artificial neural networks (ANNs) has been fabricated and tested. The chip set consists of two cascadable chips: a neuron chip and a synapse chip. Neurons on the neuron chips can be interconnected at random via synapses on the synapse chips thus implementing an ANN with arbitrary topology. The neuron test chip contains an array of 4 neurons with well defined hyperbolic tangent activation functions which is implemented by using parasitic lateral bipolar transistors. The synapse test chip is a cascadable 4×4 matrix-vector multiplier with variable, 10-b resolution matrix elements. The propagation delay of the test chips was measured to 2.6 μs per layer
Keywords :
CMOS integrated circuits; analogue processing circuits; neural chips; 2.6 mus; ANN; analog CMOS chip set; arbitrary topologies; cascadable chips; hyperbolic tangent activation functions; matrix elements; matrix-vector multiplier; neural networks; neuron chip; parasitic lateral bipolar transistors; propagation delay; synapse chip; Artificial neural networks; Bipolar transistors; MOSFETs; Network topology; Neural networks; Neurofeedback; Neurons; Testing; Very large scale integration; Voltage;
Journal_Title :
Neural Networks, IEEE Transactions on