Memristors have been suggested as a novel route to neuromorphic computing
based on the similarity between them and neurons (specifically synapses and ion
pumps). The d.c. action of the memristor is a current spike which imparts a
short-term memory to the device. Here it is demonstrated that this short-term
memory works exactly like habituation (e.g. in \emph{Aplysia}). We elucidate
the physical rules, based on energy conservation, governing the interaction of
these current spikes: summation, bounce-back', directionality and diminishing
returns’. Using these rules, we introduce 4 different logical systems to
implement sequential logic in the memristor and demonstrate how sequential
logic works by instantiating a NOT gate, an AND gate, an XOR gate and a Full
Adder with a single memristor. The Full Adder makes use of the memristor’s
short-term memory to add together three binary values and outputs the sum, the
carry digit and even the order they were input in. A memristor full adder also
outputs the arithmetical sum of bits, allowing for a logically (but not
physically) reversible system. Essentially, we can replace an input/output port
with an extra time-step, allowing a single memristor to do a hither-to
unexpectedly large amount of computation. This makes up for the memristor’s
slow operation speed and may relate to how neurons do a similarly-large
computation with such slow operations speeds. We propose that using spiking
logic, either in gates or as neuron-analogues, with plastic rewritable
connections between them, would allow the building of a neuromorphic computer.

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