no code implementations • 3 Jun 2023 • Andrei Velichko, Petr Boriskov, Maksim Belyaev, Vadim Putrolaynen
The study presents a bio-inspired chaos sensor model based on the perceptron neural network for the estimation of entropy of spike train in neurodynamic systems.
no code implementations • 7 Jan 2020 • Alexander Pergament, Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen
With a decrease in dimensions, a decrease in the thermal coupling action radius is observed, which can vary in the range from 0. 5 to 50 {\mu}m for structures with characteristic dimensions of 0. 1 to 5 {\mu}m, respectively.
Applied Physics Disordered Systems and Neural Networks
no code implementations • 7 Jan 2020 • Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen, Alexander Pergament, Valentin Perminov
In the present paper, we report on the switching dynamics of both single and coupled VO2-based oscillators, with resistive and capacitive coupling, and explore the capability of their application in oscillatory neural networks.
no code implementations • 6 Jan 2020 • Andrei Velichko, Maksim Belyaev, Vadim Putrolaynen, Valentin Perminov, Alexander Pergament
In the case of a "weak" coupling, synchronization is accompanied by attraction effect and decrease of the main spectra harmonics width.
no code implementations • 10 Apr 2018 • Andrei Velichko, Vadim Putrolaynen, Maksim Belyaev
In the circuit of two thermally coupled VO2 oscillators, we studied a higher order synchronization effect, which can be used in object classification techniques to increase the number of possible synchronous states of the oscillator system.