  Memristor-based oscillator is becoming promising thanks to its inherent NDR
(Negative Differential Region) property and compact circuit structure. This
paves the way to the large scale oscillatory neural network (ONN) and the
realization of pattern recognition based on its global synchronization.
However, the simulation of large scale ONN encounters the problem of long
simulation time because of the large number of oscillators. Here we propose a
highly efficient method to abstract the phase sensitivity characteristic of the
memristor-based oscillator, i.e., its PPV (Perturbation Projection Vector),
which allows reducing considerably the complexity of ONN simulation, and
speeding up the simulation more than 2000 times. Our study also reveals the
impact of the circuit parameters on the pattern recognition accuracy and the
robustness against the frequency mismatch.
