Neuromorphic Computing

Neuromorphic systems use electronic circuits designed to replicate the way biological neurons process information. These systems typically use spiking neural networks, analog or mixed-signal circuits, and novel memory architectures like memristors. They aim to achieve the energy efficiency and adaptability of biological brains while performing cognitive tasks. Current implementations focus on event-driven processing, parallel computation, and local learning rules.

Real-time sensory processing, autonomous systems, brain-computer interfaces, low-power AI applications, robotics