STDP learning rule based on memristor with STDP property
Publication
, Conference
Chen, L; Li, C; Huang, T; He, X; Li, H; Chen, Y
Published in: Proceedings of the International Joint Conference on Neural Networks
September 3, 2014
Spike-timing-dependent plasticity (STDP) learning ability has been observed in physical memristors, but whether the STDP is caused by the neuron or the memristor is unclear. In this paper, we proved the STDP property in the model for both symmetric and asymmetric memristor. We also employed the symmetric/asymmetric memristors with STDP property and the simplified neurons to perform the STDP learning ability. At last, the sequence learning experiment of the memritive neural network (MNN) with the symmetric memristor synapse further verifies the STDP learning ability of the memristor.
Duke Scholars
Published In
Proceedings of the International Joint Conference on Neural Networks
DOI
ISBN
9781479914845
Publication Date
September 3, 2014
Start / End Page
1 / 6
Citation
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Chen, L., Li, C., Huang, T., He, X., Li, H., & Chen, Y. (2014). STDP learning rule based on memristor with STDP property. In Proceedings of the International Joint Conference on Neural Networks (pp. 1–6). https://doi.org/10.1109/IJCNN.2014.6889506
Chen, L., C. Li, T. Huang, X. He, H. Li, and Y. Chen. “STDP learning rule based on memristor with STDP property.” In Proceedings of the International Joint Conference on Neural Networks, 1–6, 2014. https://doi.org/10.1109/IJCNN.2014.6889506.
Chen L, Li C, Huang T, He X, Li H, Chen Y. STDP learning rule based on memristor with STDP property. In: Proceedings of the International Joint Conference on Neural Networks. 2014. p. 1–6.
Chen, L., et al. “STDP learning rule based on memristor with STDP property.” Proceedings of the International Joint Conference on Neural Networks, 2014, pp. 1–6. Scopus, doi:10.1109/IJCNN.2014.6889506.
Chen L, Li C, Huang T, He X, Li H, Chen Y. STDP learning rule based on memristor with STDP property. Proceedings of the International Joint Conference on Neural Networks. 2014. p. 1–6.
Published In
Proceedings of the International Joint Conference on Neural Networks
DOI
ISBN
9781479914845
Publication Date
September 3, 2014
Start / End Page
1 / 6