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Memristor-based synapse design and a case study in reconfigurable systems

Publication ,  Conference
Ji, F; Li, HH; Wysocki, B; Thiem, C; McDonald, N
Published in: Proceedings of the International Joint Conference on Neural Networks
December 1, 2013

Scientists have dreamed of an information system with cognitive human-like skills for years. However, constrained by the device characteristics and rapidly increasing design complexity under the traditional processing technology, little progress has been made in hardware implementation. The recently popularized memristor offers a potential breakthrough for neuromorphic computing because of its unique properties including nonvolatily, extremely high fabrication density, and sensitivity to historic voltage/current behavior. In this work, we first investigate the memristor-based synapse design and the corresponding training scheme. Then, a case study of an 8-bit arithmetic logic unit (ALU) design is used to demonstrate the hardware implementation of reconfigurable system built based on memristor synapses. © 2013 IEEE.

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Proceedings of the International Joint Conference on Neural Networks

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Publication Date

December 1, 2013
 

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Ji, F., Li, H. H., Wysocki, B., Thiem, C., & McDonald, N. (2013). Memristor-based synapse design and a case study in reconfigurable systems. In Proceedings of the International Joint Conference on Neural Networks. https://doi.org/10.1109/IJCNN.2013.6706776
Ji, F., H. H. Li, B. Wysocki, C. Thiem, and N. McDonald. “Memristor-based synapse design and a case study in reconfigurable systems.” In Proceedings of the International Joint Conference on Neural Networks, 2013. https://doi.org/10.1109/IJCNN.2013.6706776.
Ji F, Li HH, Wysocki B, Thiem C, McDonald N. Memristor-based synapse design and a case study in reconfigurable systems. In: Proceedings of the International Joint Conference on Neural Networks. 2013.
Ji, F., et al. “Memristor-based synapse design and a case study in reconfigurable systems.” Proceedings of the International Joint Conference on Neural Networks, 2013. Scopus, doi:10.1109/IJCNN.2013.6706776.
Ji F, Li HH, Wysocki B, Thiem C, McDonald N. Memristor-based synapse design and a case study in reconfigurable systems. Proceedings of the International Joint Conference on Neural Networks. 2013.

Published In

Proceedings of the International Joint Conference on Neural Networks

DOI

Publication Date

December 1, 2013