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Simulation of cells for signals intensity transformation in mixed image processors and activation functions of neurons in neural networks

dc.contributor.authorKrasilenko, V. G.en
dc.contributor.authorLazarev, A. A.en
dc.contributor.authorNikitovich, D. V.en
dc.date.accessioned2022-02-04T07:53:05Z
dc.date.available2022-02-04T07:53:05Z
dc.date.issued2021
dc.description.abstractThe paper considers results of design, simulation of continuously logical pixel cells (CLPC) based on current mirrors (CM) with functions of preliminary analogue processing for image intensity transformation and coding for construction of mixed image processors (IP) and neural networks (NN). The methodology and principles of construction of such cells are based on the use of piecewise-linear approximation of functions for nonlinear transformation of analog signals. It is shown that for the realization of generalized arbitrary functions by such gamma correctors, it is possible to apply basic step functions with controlled parameters. To implement the basic step functions, it is proposed to use nodes that perform a continuous-logical operation of a limited current difference and are quite simply implemented on current reflectors (VDS). The design and modeling of continuous-logical pixel cells (CLPC) based on VDS in different modes and for different conversion functions. Such CLC has a number of advantages: high speed and reliability, simplicity, small power consumption, high integration level for linear and matrix structures. We show design of CLC variants for photocurrents transformation and their simulations. The basic element of such cells is a scheme that implements the operation of a bounded difference of continuous logic. Using a set of circuits implemented on CMOS technology, we consider generalized methods for designing cells for nonlinear conversion of the photocurrent intensity. ion of the appropriate parameters, which can be specified as constructive constants or as parameters for external control, allows changing type of synthesized functions. Possibilities of synthesis by such cells of functions with descending sections and different types are shown: sigmoid, lambda and others. Such CLPCs consist of several dozen CMOS transistors, have low power supply voltage (1.8 ÷ 3.3V), the range of an input photocurrent is 0.1÷24μA, the transformation time is less than 1 μs, low power consumption (microwatts). The circuits and the simulation results of their design with OrCAD are shown. Examples of nonlinear image transformations are given.en
dc.identifier.citationKrasilenko V. G. Simulation of cells for signals intensity transformation in mixed image processors and activation functions of neurons in neural networks [Text] / V. G. Krasilenko, A. A. Lazarev, D. V. Nikitovich // Вісник Хмельницького національного університету. Серія "Технічні науки". – 2021. – № 5. – С. 127-135.en
dc.identifier.doi10.31891/2307-5732
dc.identifier.issn2307-5732
dc.identifier.udc637.5.02
dc.identifier.urihttp://ir.lib.vntu.edu.ua/handle/123456789/35089
dc.language.isoenen
dc.publisherХмельницький національний університетuk
dc.relation.ispartofВісник Хмельницького національного університету. № 5 : 127-135.uk
dc.relation.ispartofseriesТехнічні наукиuk
dc.subjectself-learning equivalent-convolutional neural structuresen
dc.subjectequivalent modelsen
dc.subjectcontinuous-logical operationsen
dc.titleSimulation of cells for signals intensity transformation in mixed image processors and activation functions of neurons in neural networksen
dc.title.alternativeМоделювання комірок для перетворення інтенсивності сигналів у гібридних процесорах зображень та реалізації функцій активації нейронів у нейронних мережахuk
dc.typeArticle

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