Oscillator Circuit for Spike Neural Network with Sigmoid Like Activation Function and Firing Rate Coding
arXiv:1911.10351 · doi:10.1109/TCSII.2020.2997117
Abstract
The study presents an oscillator circuit for a spike neural network with the possibility of firing rate coding and sigmoid-like activation function. The circuit contains a switching element with an S-shaped current-voltage characteristic and two capacitors; one of the capacitors is shunted by a control resistor. The circuit is characterised by a strong dependence of the frequency of relaxation oscillations on the magnitude of the control resistor. The dependence has a sigmoid-like form and we present an analytical method for dependence calculation. Finally, we describe the concept of the spike neural network architecture with firing rate coding based on the presented circuit for creating neuromorphic devices and artificial intelligence.
arXiv comment9 pages, 8 figures. in IEEE Transactions on Circuits and Systems II: Express Briefs
References in corpus (6)
- Deep Learning in Spiking Neural Networks
- Challenges in materials and devices for Resistive-Switching-based Neuromorphic Computing
- A Model of an Oscillatory Neural Network with Multilevel Neurons for Pattern Recognition and Computing
- Electrical switching and oscillations in vanadium dioxide
- Switch Elements with S-Shaped Current-Voltage Characteristic in Models of Neural Oscillators
- The non-capacitor model of leaky integrate-and-fire neuron with the thermal mechanism of the membrane potential