Abstract:
Despite demonstrating exceptional performance in optical networks, neural networks often receive criticism due to their significant computational complexity. To address t...Show MoreMetadata
Abstract:
Despite demonstrating exceptional performance in optical networks, neural networks often receive criticism due to their significant computational complexity. To address this, we propose a novel relative-neural-activity-based algorithm to optimize neural networks for low computational complexity and memory footprint for failure management in optical networks, with failure identification as the considered use-case. The results suggest up to 96.31% and 87.12% reduction in computational and memory requirements, respectively.
Date of Conference: 06-09 May 2024
Date Added to IEEE Xplore: 11 July 2024
ISBN Information: