Realization of desired digital spike-trains by a simple evolutionary algorithm

Author:

Saito Toshimichi1,Yamaoka Kei1,Hamaguchi Tomoki1

Affiliation:

1. EE Dept., Hosei University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Rehabilitation,Physical Therapy, Sports Therapy and Rehabilitation,General Medicine

Reference22 articles.

1. [1] E.M. Izhikevich, Dynamical systems in neuroscience, MIT Press, 2006.

2. [2] H. Torikai, A. Funew, and T. Saito, “Digital spiking neuron and its learning for approximation of various spike-trains,” Neural Networks, vol. 21, pp. 140-149, 2008.

3. [3] T. Iguchi, A. Hirata, and H. Torikai, “Theoretical and heuristic synthesis of digital spiking neurons for spike-pattern-division multiplexing,” IEICE Trans. Fundamentals, vol. E93-A, no. 8, pp. 1486-1496, 2010.

4. [4] S.R. Campbell, D. Wang, and C. Jayaprakash, “Synchrony and desynchrony in integrate-and-fire oscillators,” Neural Comput., vol. 11, pp. 1595-1619, 1999.

5. [5] N.F. Rulkov, M.M. Sushchik, L.S. Tsimring, and A.R. Volkovskii, “Digital communication using chaotic-pulse-position modulation,” IEEE Trans. CAS-I, vol. 48, no. 12, pp. 1436-1444, 2001.

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1. A simple multiobjective evolutionary algorithm for design of digital maps;Nonlinear Theory and Its Applications, IEICE;2019

2. Multi-Phase Synchronization Phenomena in a Ring-Coupled System of Digital Spiking Neurons;IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences;2019-01-01

3. A Ladder-Type Digital Spiking Neural Network;Neural Information Processing;2018

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