International Journal of Mathematics and Mathematical Sciences
Volume 16 (1993), Issue 4, Pages 805-810
doi:10.1155/S0161171293001000
Theta function identities from optical neural network transformations
E. Elizade
and A. Romeo
Department E.C.M., Faculty of Physics, University of Barcelona, Diagonal 647, Barcelona 08028, Spain
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.