Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Mechanism for forming internal correlation when concepts are generated on a neural network with connections produced by Fourier holography

Not Accessible

Your library or personal account may give you access

Abstract

The interaction of two competing mechanisms that participate in the formation of a concept is considered in developing an approach to the implementation of inductive generalization in a Fourier-holography setup as a method of generating abstract concepts on the basis of sensory-pattern processing. These mechanisms are nonlinear iterative mapping in the correlation plane, which breaks down the internal correlation of the concept, and diffraction on a rerecorded hologram, which restores the internal correlation. It is shown that the characteristics of the index (reference) pattern that represents reality and the characteristics of the hologram, determined by the properties of the recording medium and by the method of recording it, have an effect on the formation of the internal correlation of the generated concept that prevails over the characteristics of the iterative mapping.

© 2013 Optical Society of America

PDF Article
More Like This
Computer holography using deep neural network with Fourier basis

Runze Zhu, Lizhi Chen, and Hao Zhang
Opt. Lett. 48(9) 2333-2336 (2023)

Asymmetrical neural network for real-time and high-quality computer-generated holography

Guangwei Yu, Jun Wang, Huan Yang, Zicheng Guo, and Yang Wu
Opt. Lett. 48(20) 5351-5354 (2023)

Advancing Fourier: space–time concepts in ultrafast optics, imaging, and photonic neural networks

Luc Froehly, François Courvoisier, Daniel Brunner, Laurent Larger, Fabrice Devaux, Eric Lantz, John M. Dudley, and Maxime Jacquot
J. Opt. Soc. Am. A 36(11) C69-C77 (2019)

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 Optica member, or as an authorized user of your institution.

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

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.