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Theta function identities from optical neural network transformations

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  • E. Elizalde
  • A. Romeo

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.

Suggested Citation

  • E. Elizalde & A. Romeo, 1993. "Theta function identities from optical neural network transformations," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 16, pages 1-6, January.
    • Handle: RePEc:hin:jijmms:674139
    DOI: 10.1155/S0161171293001000
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