  As an extension of the pairwise spike-timing-dependent plasticity (STDP)
learning rule, the triplet STDP is provided with greater capability in
characterizing the synaptic changes in the biological neural cell. In this
work, a novel mixed-signal circuit scheme, called multiple-step quantized
triplet STDP, is designed to provide a precise and flexible implementation of
coactivation triplet STDP learning rule in memristive synapse spiking neural
network. The robustness of the circuit is greatly improved through the
utilization of pulse-width encoded weight modulation signals. The circuit
performance is studied through the simulations which are carried out in MATLAB
Simulink & Simscape, and assessment is given by comparing the results of
circuits with the algorithmic approaches.
