Emergence of competitive control in a memristor-based neuromorphic circuit

Recent work in neuroscience is revealing how the blowfly rapidly detects orientation using neural circuits distributed directly behind its photo receptors. These circuits like all biological systems rely on timing, competition, feedback, and energy optimization. The recent realization of the passive memristor device, the so-called fourth fundamental passive element of circuit theory, assists with making low power biologically inspired parallel analog computation achievable. Building on these developments, we present a memristor-based neuromorphic competitive control (mNCC) circuit, which utilizes a single sensor and can control the output of N actuators delivering optimal scalable performance, and immunity from device variation and environmental noise.