000082357 001__ 82357
000082357 005__ 20180317093225.0
000082357 037__ $$aCONF
000082357 245__ $$aA Method for All-Positive Optical Multilayer Perceptrons
000082357 269__ $$a1996
000082357 260__ $$aPiscataway, NJ$$bIEEE$$c1996
000082357 336__ $$aConference Papers
000082357 520__ $$aThe most promising approaches for optical neural networks are based on intensity encoding. However, a serious drawback of intensity encoding is the lack of negative values and optical subtraction, which are essential for rendering neural networks useful. To overcome the need for optical subtraction a novel training method is described here that is especially useful for optical multilayer neural networks. In this method, subtraction is implemented as a transformation of the interconnection weights which makes possible the implementation of multilayer perceptrons with optical thresholding. The method is straightforward to implement in optical neural networks where learning occurs under external electronic/computer control.
000082357 6531_ $$aneuron
000082357 6531_ $$alearning
000082357 700__ $$aSaxena, Indu
000082357 700__ $$aFiesler, Emile
000082357 700__ $$aMoerland, Perry
000082357 7112_ $$aUniversity of Patras - Proceedings of the Third IEEE International Conference on Electronics, Circuits, and Systems$$cRhodos, Greece
000082357 773__ $$j1$$q448-451$$tProceedings of the Third IEEE International Conference on Electronics, Circuits, and Systems
000082357 8564_ $$uhttp://publications.idiap.ch/downloads/reports/1996/icecs96.pdf$$zURL
000082357 8564_ $$s115555$$uhttps://infoscience.epfl.ch/record/82357/files/icecs96.pdf$$zn/a
000082357 909CO $$ooai:infoscience.tind.io:82357$$pSTI$$pconf
000082357 909C0 $$0252189$$pLIDIAP$$xU10381
000082357 937__ $$aEPFL-CONF-82357
000082357 970__ $$aSaxena-96/LIDIAP
000082357 973__ $$aEPFL$$sPUBLISHED
000082357 980__ $$aCONF