Abstract:
Memristor is a computational and area efficient
substitute for resistive synapse in neural networks as it provides
tunable and non-volatile storage of synaptic weights. Full CMOS
circuit realisation of a 6 × 6 Bidirectional Associative Memory
(BAM) neural network with CMOS memristor synapse is implemented in this paper. To show the BAM neural network’s
ability to recall its pattern, we have taken the training set of
three Tetris pattern pairs, and corresponding synapse weights
are calculated using MATLAB. We have integrated the proposed
tunable CMOS memristor emulator in the crossbar for storing
the synaptic weights. The CMOS circuit implementation of the
BAM neural network is validated with the simulation results in
0.18µm CMOS technology.
