Abstract

Binary classification of an object in a two-dimensional image is considered. A spatial light rebroadcaster is shown to be advantageous for learning in this case because it can store the weights and permit upward and downward adjustments. Two learning algorithms, based on the perceptron, are considered. A modification of the perceptron algorithm is developed so that only positive weights are needed. This is convenient because light intensity is positive only. The modified algorithm is shown to converge in a finite number of steps for positive linear separable classes. Optical experiments show the classification of four characters in two groups, in which alternative groupings are used to show robustness. In the second group of experiments the complements of the two-dimensional characters are used, and the convergence is equally fast. Adding the results from the original and complementary patterns provides a discrimination superior to that obtained using either on its own.

© 1993 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Optical neural networks: an introduction by the feature editors

Kelvin Wagner and Demetri Psaltis
Appl. Opt. 32(8) 1261-1263 (1993)

Optical implementations of radial basis classifiers

Mark A. Neifeld and Demetri Psaltis
Appl. Opt. 32(8) 1370-1379 (1993)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (14)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (26)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription