Publications by authors named "Nassim Abderrahmane"
Article Synopsis
- Machine learning has gained significant traction in both research and industry, especially in areas like image classification, but its reliance on large computing power makes it less suitable for embedded systems.
- To address this, researchers are exploring brain-inspired computing as an energy-efficient alternative to traditional CPU/GPU systems, focusing on designing adaptable neuromorphic hardware for parallel and distributed computations.
- The paper introduces a framework for neuromorphic hardware design, along with a simulator named NAXT, to optimize Spiking Neural Networks by modifying coding techniques to reduce spike events, thereby lowering power consumption while maintaining performance.
