Testing and Reliability of Spiking Neural Networks: A Review of the State-of-the-Art
Abstract
Neuromorphic computing based on Spiking Neural Networks (SNNs) is an emerging computing paradigm inspired by the functionality of the biological brain. Given its potential to revolutionize the power efficiency of many Artificial Intelligence (AI) applications, heavy research is underway on algorithms, hardware implementations, and applications. This article focuses on testing and reliability of hardware implementations providing a review of the state-of-the-art.
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