Impact of Noisy Input on Evolved Spiking Neural Networks for Neuromorphic Systems

Author:

Patel Karan P.1ORCID,Schuman Catherine D.1ORCID

Affiliation:

1. University of Tennessee, United States

Funder

U.S. Department of Energy

Publisher

ACM

Reference17 articles.

1. Ali BanaGozar , Mohammad Ali Maleki , Mehdi Kamal , Ali Afzali-Kusha , and Massoud Pedram . 2017 . Robust neuromorphic computing in the presence of process variation. In Design , Automation & Test in Europe Conference & Exhibition (DATE) , 2017. IEEE, 440–445. Ali BanaGozar, Mohammad Ali Maleki, Mehdi Kamal, Ali Afzali-Kusha, and Massoud Pedram. 2017. Robust neuromorphic computing in the presence of process variation. In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017. IEEE, 440–445.

2. Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. Openai gym. arXiv preprint arXiv:1606.01540(2016). Greg Brockman Vicki Cheung Ludwig Pettersson Jonas Schneider John Schulman Jie Tang and Wojciech Zaremba. 2016. Openai gym. arXiv preprint arXiv:1606.01540(2016).

3. Julian Büchel , Dmitrii Zendrikov , Sergio Solinas , Giacomo Indiveri , and Dylan  R Muir . 2021. Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors. Scientific reports 11, 1 ( 2021 ), 1–12. Julian Büchel, Dmitrii Zendrikov, Sergio Solinas, Giacomo Indiveri, and Dylan R Muir. 2021. Supervised training of spiking neural networks for robust deployment on mixed-signal neuromorphic processors. Scientific reports 11, 1 (2021), 1–12.

4. Mihaela Dimovska , Travis Johnston , Catherine  D Schuman , J Parker Mitchell , and Thomas  E Potok . 2019 . Multi-objective optimization for size and resilience of spiking neural networks. In 2019 IEEE 10th Annual Ubiquitous Computing , Electronics & Mobile Communication Conference (UEMCON). IEEE, 0433–0439 . Mihaela Dimovska, Travis Johnston, Catherine D Schuman, J Parker Mitchell, and Thomas E Potok. 2019. Multi-objective optimization for size and resilience of spiking neural networks. In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON). IEEE, 0433–0439.

5. Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems

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