Synchronous versus sequential updating in the three-state Ising neural network with variable dilution

Details Synchronous versus sequential updating in the three-state Ising neural network with variable dilution Synchronous versus sequential updating in the three-state Ising neural network with variable dilution

2005-07-19

arxiv.org/abs/cond-mat/0507444v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

21 pages Latex, 12 eps figures and 1 ps figure

Scientific paper

10.1016/j.physa.2005.12.052

The three-state Ising neural network with synchronous updating and variable dilution is discussed starting from the appropriate Hamiltonians. The thermodynamic and retrieval properties are examined using replica mean-field theory. Capacity-temperature phase diagrams are derived for several values of the pattern activity and different gradations of dilution, and the information content is calculated. The results are compared with those for sequential updating. The effect of self-coupling is established. Also the dynamics is studied using the generating function technique for both synchronous and sequential updating. Typical flow diagrams for the overlap order parameter are presented. The differences with the signal-to-noise approach are outlined.

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