Three-state neural network: from mutual information to the Hamiltonian.
@article{Dominguez2000ThreestateNN, title={Three-state neural network: from mutual information to the Hamiltonian.}, author={D. R. Carreta Dominguez and E. Korutcheva}, journal={Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics}, year={2000}, volume={62 2 Pt B}, pages={ 2620-8 } }
The mutual information, I, of the three-state neural network can be obtained exactly for the mean-field architecture, as a function of three macroscopic parameters: the overlap, the neural activity and the activity-overlap, i.e., the overlap restricted to the active neurons. We perform an expansion of I on the overlap and the activity-overlap, around their values for neurons almost independent of the patterns. From this expansion we obtain an expression for a Hamiltonian which optimizes the… CONTINUE READING
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