Synchronization of nonlinear electronic oscillators for neural computation

This paper deals with coupled oscillators as the building blocks of a bioinspired computing paradigm and their implementation. In order to accomplish the low-power and fast-processing requirements of autonomous applications, we study the microelectronic analog implementation of physical oscillators, instead of the software computer-simulated implementation. With this aim, the original oscillator has been adapted to a suitable microelectronic form. So as to study the hardware nonlinear oscillators, we propose two macro models, demonstrating that they preserve the synchronization properties. Secondary effects such as mismatch and output delay and their relation to network synchronization are analyzed and discussed. We show the correct operation of the proposed electronic oscillators with simulations and experimental results from a manufactured integrated test circuit. The proposed architecture is intended to perform the scene segmentation stage of an autonomous focal-plane self-contained visual processing system for artificial vision applications.