Invariance in an optoelectronic implementation of neural networks

Yizhak Idan; Raymond C. Chevallier; Kevin J. Heggarty; Gabriel Y. Sirat

doi:10.1117/12.20688

1 August 1990 Invariance in an optoelectronic implementation of neural networks

Yizhak Idan, Raymond C. Chevallier, Kevin J. Heggarty, Gabriel Y. Sirat

Proceedings Volume 1281, Optical Interconnections and Networks; (1990) https://doi.org/10.1117/12.20688
Event: The International Congress on Optical Science and Engineering, 1990, The Hague, Netherlands

Abstract

Two dimensional jmuem recognition related tasks require the introduction of invariant recognition ftors such as shift, rotation, scale and deformation. In a preliminary work' we showed the inherent capability of our FMR coding to perform shift-invariant retrieval. This capability is essential for other invariances which can be transformed into translated representations. In this paper we propose using this translation invariant coding in a general scheme, whereby a we-processor handles the invariance issues and aligns the input probe to a fixed baseline utilized by the recognition mechanism. This higher order layer includes S "validation switches", each switch corresponding to a position index of translated objects. A validation switch will be eon" f the stimulus matches one of the objects, translated to the position handled by this switch. These switches condition the search, and where a search is needed, they supply the required transformation for stimulus alignment. Several proximity measures, needed for the realization of these switches, are presented and compared, in the context of different weight prescription algorithms.

Citation Download Citation

Yizhak Idan, Raymond C. Chevallier, Kevin J. Heggarty, and Gabriel Y. Sirat "Invariance in an optoelectronic implementation of neural networks", Proc. SPIE 1281, Optical Interconnections and Networks, (1 August 1990); https://doi.org/10.1117/12.20688

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