Spike train propagation in Hybrid Artificial Neural Network (HANN)
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866911448361336832 |
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| author | Yiannis, Contoyiannis. F. |
| author_facet | Yiannis, Contoyiannis. F. |
| contents | The spikes train is an important step in order to the artificial neural network (ANN) give us simulations more close to the reality i.e the operation of the biological neural network. Based on in previous our work that the HANN can to produce critical and tricritical intermittencies we investigate in present work the possibility of the Spike train production from the HANN. So the operation of ANN does not would based in mathematical algorithm of machine learning but the operation of a ANN could be based in physical notions as the phenomenon of intermittency. As we have shown the real biological neurons is a Dynamical system which present the intermittent dynamic type I. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2602_13752 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Spike train propagation in Hybrid Artificial Neural Network (HANN) Yiannis, Contoyiannis. F. Chaotic Dynamics The spikes train is an important step in order to the artificial neural network (ANN) give us simulations more close to the reality i.e the operation of the biological neural network. Based on in previous our work that the HANN can to produce critical and tricritical intermittencies we investigate in present work the possibility of the Spike train production from the HANN. So the operation of ANN does not would based in mathematical algorithm of machine learning but the operation of a ANN could be based in physical notions as the phenomenon of intermittency. As we have shown the real biological neurons is a Dynamical system which present the intermittent dynamic type I. |
| title | Spike train propagation in Hybrid Artificial Neural Network (HANN) |
| topic | Chaotic Dynamics |
| url | https://arxiv.org/abs/2602.13752 |