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Pattern recognition via Ising model with long range interactions
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...
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Published in: | Physica A 1997-08, Vol.242 (3), p.323-331 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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
N
3
2
. |
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ISSN: | 0378-4371 1873-2119 |
DOI: | 10.1016/S0378-4371(97)00288-4 |