Finite size scaling in neural networks

Details Finite size scaling in neural networks Finite size scaling in neural networks

1996-11-05

arxiv.org/abs/cond-mat/9611027v1

Physics

Condensed Matter

Disordered Systems and Neural Networks

4 pages, RevTex, 5 figures, uses multicol.sty and psfig.sty

Scientific paper

10.1103/PhysRevLett.78.555

We demonstrate that the fraction of pattern sets that can be stored in single- and hidden-layer perceptrons exhibits finite size scaling. This feature allows to estimate the critical storage capacity \alpha_c from simulations of relatively small systems. We illustrate this approach by determining \alpha_c, together with the finite size scaling exponent \nu, for storing Gaussian patterns in committee and parity machines with binary couplings and up to K=5 hidden units.

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