Pulse Coupled Neural Network

Pulse-coupled neural networks (PCNNs) are computational models inspired by the mammalian visual cortex, aiming to mimic the brain's information processing through synchronized neuronal firing. Current research focuses on improving PCNN efficiency and biological realism, exploring architectures like random-coupled neural networks (RCNNs) to reduce computational cost and incorporating PCNNs into deep learning frameworks (DPCNNs) for enhanced performance in image processing tasks. These advancements demonstrate PCNNs' potential for efficient and robust solutions in computer vision, medical imaging, and other applications requiring spatio-temporal pattern recognition, particularly where energy efficiency is crucial.