  Synchronous oscillations in neuronal ensembles have been proposed to provide
a neural basis for the information processes in the brain. In this work, we
present a neuromorphic computing algorithm based on oscillator synchronization
in a critical regime. The algorithm uses the high dimensional transient
dynamics perturbed by an input and translates it into proper output stream. One
of the benefits of adopting coupled phase oscillators as neuromorphic elements
is that the synchrony among oscillators can be finely tuned at a critical
state. Especially near a critical state, the marginally synchronized
oscillators operate with high efficiency and maintain better computing
performances. We also show that explosive synchronization which is induced from
specific neuronal connectivity produces more improved and stable outputs. This
work provides a systematic way to encode computing in a large size coupled
oscillators, which may be useful in designing neuromorphic devices.
