Abstract
A description is given of a formulation for 2-D neural nets which is suitable for the processing of 2-D array images. The formulation essentially processes a 2-D input array to be premultiplied and postmultiplied by a matrix of weights. Then the resulting 2-D array of data is processed via the usual sigmoidal thresholding and feedback, which are characteristic of neural nets. The authors describe two electrooptical implementations of their formulation: the first includes adaptations of the available incoherent optical techniques for the real-time multiplication of three matrices, while the second includes adaptations of vector-matrix multiplication and the sum of the outer product of vectors. The second requires less optical hardware for its implementation. >
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
