An Online Supervised Learning Algorithm Based on Nonlinear Spike Train Kernels

Author:

Lin Xianghong,Zhang Ning,Wang Xiangwen

Publisher

Springer International Publishing

Reference21 articles.

1. Yegnanarayana, B.: Artificial Neural Networks. PHI Learning Pvt Ltd., New Delhi (2009)

2. Ahmed, F.Y.H., Yusob, B., Hamed, H.N.A.: Computing with spiking neuron networks a review. Int. J. Adv. Soft Comput. Its Appl.s 6(1), 1–21 (2014)

3. Yu, Q., Goh, S.K., Tang, H., Tan, K.C.: Application of precise-spike-driven rule in spiking neural networks for optical character recognition. In: Handa, H., Ishibuchi, K.-C., Ong, H., Tan, K.-C. (eds.) Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems, vol. 2, pp. 65–75. Springer International Publishing, NewYork (2015)

4. Carlson, K.D., Nageswaran, J.M., Dutt, N., Krichmar, J.L.: An efficient automated parameter tuning framework for spiking neural networks. Front. Neuroscience 8, 10 (2014)

5. Bohte, S.M., Kok, J.N., La Poutre, H.: Error-backpropagation in temporally encoded networks of spiking neurons. Neurocomputing 48(1), 17–37 (2002)

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