Winner-Take-All Circuits in Neuromorphic Computing

Abstract

The increase in computational demands of Artificial Intelligence (AI) has exposed the limitations of conventional computing architectures in terms of power efficiency and scalability. Neuromorphic computing provides an alternative inspired by biological neural systems in the form of event-driven, parallel, and energy-efficient computation. Within the neuromorphic architectures, Winner-Take-All (WTA) circuits play a critical role by allowing competition and decision making in information. This review paper discusses neuromorphic computing concepts with a focus on WTA circuit architectures.