Learning of Simple Dynamic Binary Neural Networks

Author:

KOUZUKI Ryota1,SAITO Toshimichi1

Affiliation:

1. Hosei University

Publisher

Institute of Electronics, Information and Communications Engineers (IEICE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Signal Processing

Reference17 articles.

1. [1] J.J. Hopfield, “Neural networks and physical systems with emergent collective computation abilities,” Proc. National Academy of Science, vol.79, pp.2554-2558, USA, 1982.

2. [2] K. Araki and T. Saito, “An associative memory including time-variant self-feedback,” IEEE Trans. Neural Netw., vol.7, no.8, pp.1267-1271, 1994.

3. [3] K. Nowara and T. Saito, “Guaranteed storing of limit cycles into a discrete-time asynchronous neural network,” IEICE Trans. Fundamentals, vol.E75-A, no.11, pp.1579-1582, Nov. 1992.

4. [4] R. Ito and T. Saito, “Dynamic Binary Neural Networks and Evolutionary Learning,” Proc. IEEE-INNS/IJCNN, pp.1683-1687, 2010.

5. [5] R. Ito, Y. Nakayama, and T. Saito, “Analysis and learning of periodic orbits in dynamic binary neural networks,” Proc. IEEE-INNS/IJCNN, pp.502-508, 2012.

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