Abstract
This paper studies digital spike interval maps and its learning algorithm. The map can output a variety of digital spike-trains. In order to learn a desired spike-train, two maps are switched by the contradiction detector and they evolve with self-organizing and growing functions. Performing basic numerical experiments for two examples, algorithm efficiency is confirmed.
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References
Izhikevich, E.M.: Simple Model of Spiking Neurons. IEEE Trans. Neural Networks 14(6), 1569–1572 (2003)
Toyoizumi, T., Aihara, K., Amari, S.: Fisher information for spike-based population coding. Phys. Rev. Lett. 97, 098102 (2006)
Perez, R., Glass, L.: Bistability, period doubling bifurcations and chaos in a periodically forced oscillator. Phys. Lett. 90A(9), 441–443 (1982)
Torikai, H., Saito, T.: Return map quantization from an integrate-and-fire model with two periodic inputs. IEICE Trans. Fund. E82-A(7), 1336–1343 (1999)
Takahashi, Y., Nakano, H., Saito, T.: A simple hyperchaos generator based on impulsive switching. IEEE Trans. Circuits Syst. II 51(9), 468–472 (2004)
Hashimoto, S., Torikai, H.: A novel hybrid spiking neuron: bifurcations, responses, and on-chip learning. IEEE Trans. Circuits Syst. I 57(8), 2168–2181 (2010)
Campbell, S.R., Wang, D., Jayaprakash, C.: Synchrony and desynchrony in integrate-and-fire oscillators. Neural Computation 11, 1595–1619 (1999)
Sushchik, M., Rulkov, N., Larson, L., Tsimring, L., Abarbanel, H., Yao, K., Volkovskii, A.: Chaotic pulse position modulation: a robust method of communicating with chaos. IEEE Comm. Lett. 4, 128–130 (2000)
Torikai, T., Nishigami, T.: An artificial chaotic spiking neuron inspired by spiral ganglion cell. Neural Networks 22, 664–673 (2009)
Kohonen, T.: Self-organizing maps. Springer, Heidelberg (2001)
Torikai, H., Funew, A., Saito, T.: Digital spiking neuron and its learning for approximation of various spike-trains. Neural Networks 21, 140–149 (2008)
Ogawa, T., Saito, T.: Digital spike maps and learning of spike signals. In: Proc. IEEE-INNS Int’l. Joint Conf. Neural Netw., pp. 1587–1592 (2010)
Oshime, T., Saito, T., Torikai, H.: ART-Based Parallel Learning of Growing SOMs and its Application to TSP. In: King, I., Wang, J., Chan, L.-W., Wang, D. (eds.) ICONIP 2006. LNCS, vol. 4232, pp. 1004–1011. Springer, Heidelberg (2006)
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Ogawa, T., Saito, T. (2011). Self-organizing Digital Spike Interval Maps. In: Lu, BL., Zhang, L., Kwok, J. (eds) Neural Information Processing. ICONIP 2011. Lecture Notes in Computer Science, vol 7063. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24958-7_71
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DOI: https://doi.org/10.1007/978-3-642-24958-7_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24957-0
Online ISBN: 978-3-642-24958-7
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