Fault-Tolerant Spiking Neural Network Mapping Algorithm and Architecture to 3D-NoC-Based Neuromorphic Systems
Author:
Affiliation:
1. Graduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/6514899/10130549.pdf?arnumber=10130549
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1. Noise as a Resource for Computation and Learning in Networks of Spiking Neurons
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2. Reliable Fault Tolerance and Recovery for VLSI Systems;2024 International Conference on Optimization Computing and Wireless Communication (ICOCWC);2024-01-29
3. Fault Recovery in Spiking Neural Networks Through Target and Selection of Faulty Neurons for 3D Spiking Neuromorphic Processors;2023 IEEE 6th International Conference on Knowledge Innovation and Invention (ICKII);2023-08-11
4. Towards Task Mapping Approaches in Network on Chips: A Comprehensive Survey;2023-07-20
5. R-MaS3N: Robust Mapping of Spiking Neural Networks to 3D-NoC-Based Neuromorphic Systems for Enhanced Reliability;IEEE Access;2023
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