Theta function identities from optical neural network transformations
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 on...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
1993-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1155/S0161171293001000 |
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| _version_ | 1832552637339271168 |
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| author | E. Elizalde A. Romeo |
| author_facet | E. Elizalde A. Romeo |
| author_sort | E. Elizalde |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4c29cf0195ee4315905c0ade09e80c21 |
| institution | Kabale University |
| issn | 0161-1712 1687-0425 |
| language | English |
| publishDate | 1993-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-4c29cf0195ee4315905c0ade09e80c212025-02-03T05:58:16ZengWileyInternational Journal of Mathematics and Mathematical Sciences0161-17121687-04251993-01-0116480581010.1155/S0161171293001000Theta function identities from optical neural network transformationsE. Elizalde0A. Romeo1Department E.C.M., Faculty of Physics, University of Barcelona, Diagonal 647, Barcelona 08028, SpainDepartment E.C.M., Faculty of Physics, University of Barcelona, Diagonal 647, Barcelona 08028, SpainWe 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.http://dx.doi.org/10.1155/S0161171293001000Jacobi theta functionsRiemann zeta functionsneural networks computer holograms. |
| spellingShingle | E. Elizalde A. Romeo Theta function identities from optical neural network transformations International Journal of Mathematics and Mathematical Sciences Jacobi theta functions Riemann zeta functions neural networks computer holograms. |
| title | Theta function identities from optical neural network transformations |
| title_full | Theta function identities from optical neural network transformations |
| title_fullStr | Theta function identities from optical neural network transformations |
| title_full_unstemmed | Theta function identities from optical neural network transformations |
| title_short | Theta function identities from optical neural network transformations |
| title_sort | theta function identities from optical neural network transformations |
| topic | Jacobi theta functions Riemann zeta functions neural networks computer holograms. |
| url | http://dx.doi.org/10.1155/S0161171293001000 |
| work_keys_str_mv | AT eelizalde thetafunctionidentitiesfromopticalneuralnetworktransformations AT aromeo thetafunctionidentitiesfromopticalneuralnetworktransformations |