Author:
Saquib Taasin,Terzopoulos Demetri
Publisher
Springer Nature Switzerland
Reference22 articles.
1. Bekolay, T., et al.: Nengo: a Python tool for building large-scale functional brain models. Front. Neuroinformat. 7(48), 1–13 (2014)
2. Bouvier, M., et al.: Spiking neural networks hardware implementations and challenges: a survey. ACM J. on Emerging Technol. Comput. Syst. 15(2) (2019)
3. Diehl, P., Cook, M.: Unsupervised learning of digit recognition using spike-timing-dependent plasticity. Front. Comput. Neurosci. 9 (2015)
4. Diehl, P.U., Neil, D., Binas, J., Cook, M., Liu, S.C., Pfeiffer, M.: Fast-classifying, high-accuracy spiking deep networks through weight and threshold balancing. In: 2015 International Joint Conference on Neural Networks (IJCNN), pp. 1–8 (2015)
5. Eshraghian, J.K., et al.: Training spiking neural networks using lessons from deep learning. arXiv preprint arXiv:2109.12894 (2021)
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