Theta function identities from optical neural network transformations

E. Elizalde and A. Romeo

International Journal of Mathematics and Mathematical Sciences, 1993, vol. 16, 1-6

Abstract:

We take a new approach to the generation of Jacobi theta function identities. It is complementary to the procedure which makes use of the evaluation of Parseval-like identities for elementary cylindrically-symmetric functions on computer holograms. Our method is more simple and explicit than this one, which was an outcome of the construction of neurocomputer architectures through the Heisenberg model.

Date: 1993
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jijmms:674139

DOI: 10.1155/S0161171293001000

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