Design and simulation of optoelectronic complementary dual neural elements for realizing a family of normalized vector 'equivalence-nonequivalence' operations

Vladimir G. Krasilenko; Aleksandr I. Nikolsky; Alexander A. Lazarev; Taras E. Magas

doi:10.1117/12.850871

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12 April 2010 Design and simulation of optoelectronic complementary dual neural elements for realizing a family of normalized vector 'equivalence-nonequivalence' operations

Vladimir G. Krasilenko, Aleksandr I. Nikolsky, Alexander A. Lazarev, Taras E. Magas

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Proceedings Volume 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII; 77030P (2010) https://doi.org/10.1117/12.850871
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

Equivalence models (EM) advantages of neural networks (NN) are shown in paper. EMs are based on vectormatrix procedures with basic operations of continuous neurologic: normalized vector operations "equivalence", "nonequivalence", "autoequivalence", "autononequivalence". The capacity of NN on the basis of EM and of its modifications, including auto-and heteroassociative memories for 2D images, exceeds in several times quantity of neurons. Such neuroparadigms are very perspective for processing, recognition, storing large size and strongly correlated images. A family of "normalized equivalence-nonequivalence" neuro-fuzzy logic operations on the based of generalized operations fuzzy-negation, t-norm and s-norm is elaborated. A biologically motivated concept and time pulse encoding principles of continuous logic photocurrent reflexions and sample-storage devices with pulse-width photoconverters have allowed us to design generalized structures for realization of the family of normalized linear vector operations "equivalence"-"nonequivalence". Simulation results show, that processing time in such circuits does not exceed units of micro seconds. Circuits are simple, have low supply voltage (1-3 V), low power consumption (milliwatts), low levels of input signals (microwatts), integrated construction, satisfy the problem of interconnections and cascading.

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Vladimir G. Krasilenko, Aleksandr I. Nikolsky, Alexander A. Lazarev, and Taras E. Magas "Design and simulation of optoelectronic complementary dual neural elements for realizing a family of normalized vector 'equivalence-nonequivalence' operations", Proc. SPIE 7703, Independent Component Analyses, Wavelets, Neural Networks, Biosystems, and Nanoengineering VIII, 77030P (12 April 2010); https://doi.org/10.1117/12.850871

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