Pattern recognition via Ising model with long range interactions

Borko D. Stošić and Ivon P. Fittipaldi

Physica A: Statistical Mechanics and its Applications, 1997, vol. 242, issue 3, 323-331

Abstract: We present a novel approach to pattern recognition, based on mapping of images onto a multidimensional parameter space defined by a long range interaction Ising model Hamiltonian. It is shown that different character patterns occupy mutually distant points within the n-dimensional space defined by a test Hamiltonian with n terms, while similar patterns occupy nearby points. By the appropriate choice of the test Hamiltonian, the approach is adjustable to various symmetry considerations, and, as opposed to neural networks, it is not hindered by pattern storage capacity. The computational effort required for recognition of one character composed of N pixels is proportional to N32.

Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:242:y:1997:i:3:p:323-331

DOI: 10.1016/S0378-4371(97)00288-4

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