The three-dimensional rotation neural network

J.W. Shuai, J.C. Zheng, Z.X. Chen, R.T. Liu and B.X. Wu

Physica A: Statistical Mechanics and its Applications, 1997, vol. 238, issue 1, 23-38

Abstract: The storage capacity of the three-dimensional rotation neural network model is discussed by using the signal-to-noise theory. Some results discussed in the Hopfield model, the complex phasor model and the Hamilton neural network are obtained. Compared to other multistate neural networks, a novel property of the model is that the storage capacity for a fixed neuronal state varies with the different combinations of numbers of rotation angles and axes. The maximum storage capacity can be obtained for a special combination of numbers of rotation angles and axes.

Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:238:y:1997:i:1:p:23-38

DOI: 10.1016/S0378-4371(96)00465-7

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