Statics and dynamics of an Ashkin-Teller neural network with low loading

Details Statics and dynamics of an Ashkin-Teller neural network with low loading Statics and dynamics of an Ashkin-Teller neural network with low loading

1998-01-27

arxiv.org/abs/cond-mat/9801284v2

J. Phys. A: Math. Gen. 31 (1998) 6319-6332

Physics

Condensed Matter

Disordered Systems and Neural Networks

20 pages, 6 figures, Latex with postscript figures in one tar.gz file

Scientific paper

10.1088/0305-4470/31/30/002

An Ashkin-Teller neural network, allowing for two types of neurons is considered in the case of low loading as a function of the strength of the respective couplings between these neurons. The storage and retrieval of embedded patterns built from the two types of neurons, with different degrees of (in)dependence is studied. In particular, thermodynamic properties including the existence and stability of Mattis states are discussed. Furthermore, the dynamic behaviour is examined by deriving flow equations for the macroscopic overlap. It is found that for linked patterns the model shows better retrieval properties than a corresponding Hopfield model.

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