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Design and simulation of programmable relational optoelectronic time-pulse coded processors as base elements for sorting neural networks
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Paper Abstract

In the paper we show that the biologically motivated conception of time-pulse encoding usage gives a set of advantages (single methodological basis, universality, tuning simplicity, learning and programming et al) at creation and design of sensor systems with parallel input-output and processing for 2D structures hybrid and next generations neuro-fuzzy neurocomputers. We show design principles of programmable relational optoelectronic time-pulse encoded processors on the base of continuous logic, order logic and temporal waves processes. We consider a structure that execute analog signal extraction, analog and time-pulse coded variables sorting. We offer optoelectronic realization of such base relational order logic element, that consists of time-pulse coded photoconverters (pulse-width and pulse-phase modulators) with direct and complementary outputs, sorting network on logical elements and programmable commutation blocks. We make technical parameters estimations of devices and processors on such base elements by simulation and experimental research: optical input signals power 0.2 - 20 uW, processing time 1 - 10 us, supply voltage 1 - 3 V, consumption power 10 - 100 uW, extended functional possibilities, learning possibilities. We discuss some aspects of possible rules and principles of learning and programmable tuning on required function, relational operation and realization of hardware blocks for modifications of such processors. We show that it is possible to create sorting machines, neural networks and hybrid data-processing systems with untraditional numerical systems and pictures operands on the basis of such quasiuniversal hardware simple blocks with flexible programmable tuning.

Paper Details

Date Published: 5 May 2010
PDF: 9 pages
Proc. SPIE 7723, Optics, Photonics, and Digital Technologies for Multimedia Applications, 77231G (5 May 2010); doi: 10.1117/12.851574
Show Author Affiliations
Vladimir G. Krasilenko, Vinnitsa Social Economy Institute (Ukraine)
Alexander I. Nikolsky, Vinnitsa State Technical Univ. (Ukraine)
Alexander A. Lazarev, Vinnitsa State Technical Univ. (Ukraine)
Maria V. Lazareva, Vinnitsa Social Economy Institute (Ukraine)

Published in SPIE Proceedings Vol. 7723:
Optics, Photonics, and Digital Technologies for Multimedia Applications
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal; Frédéric Truchetet; Pasi Saarikko, Editor(s)

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