  We explore a prototype of an oscillatory neural network (ONN) based on
vanadium dioxide switching devices. The model system under study represents two
oscillators based on thermally coupled VO2 switches. Numerical simulation shows
that the effective action radius RTC of coupling depends both on the total
energy released during switching and on the average power. It is experimentally
and numerically proved that the temperature change dT commences almost
synchronously with the released power peak and T-coupling reveals itself up to
a frequency of about 10 kHz. For the studied switching structure configuration,
the RTC value varies over a wide range from 4 to 45 mkm, depending on the
external circuit capacitance C and resistance Ri, but the variation of Ri is
more promising from the practical viewpoint. In the case of a "weak" coupling,
synchronization is accompanied by attraction effect and decrease of the main
spectra harmonics width. In the case of a "strong" coupling, the number of
effects increases, synchronization can occur on subharmonics resulting in
multilevel stable synchronization of two oscillators. An advanced algorithm for
synchronization efficiency and subharmonic ratio calculation is proposed. It is
shown that of the two oscillators the leading one is that with a higher main
frequency, and, in addition, the frequency stabilization effect is observed.
Also, in the case of a strong thermal coupling, the limit of the supply current
parameters, for which the oscillations exist, expands by ~ 10 %. The obtained
results have a universal character and open up a new kind of coupling in ONNs,
namely, T-coupling, which allows for easy transition from 2D to 3D integration.
The effect of subharmonic synchronization hold promise for application in
classification and pattern recognition.
