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Capacity of neural networks with discrete synaptic couplings

H Gutfreund and Y Stein

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The authors study the optimal storage capacity of neural networks with discrete local constraints on the synaptic couplings Jij. Models with such constraints include those with binary couplings Jij=+or-1 or Jij=0, 1, quantised couplings with larger synaptic range, e.g. Jij=+or-1/L, +or-2/L, . . ., +or-1 and, in the limit, continuous couplings confined to the hypercube mod Jij mod <or=1 ('box confinement'). They find that the optimal storage capacity alpha ( kappa ) is best determined by the vanishing of a suitably defined 'entropy' as calculated in the replica symmetric approximation. They also extend their results to cases with biased memories and make contact with sparse coding models.


PACS

05.50.+q Lattice theory and statistics (Ising, Potts, etc.)

05.45.-a Nonlinear dynamics and nonlinear dynamical systems

05.70.Ce Thermodynamic functions and equations of state

MSC

82C32 Neural nets (See also 68T05, 91E40, 92B20)

82C20 Dynamic lattice systems (kinetic Ising, etc.) and systems on graphs

Subjects

Statistical physics and nonlinear systems

Dates

Issue 12 (21 June 1990)



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