{"id":11338,"date":"2022-03-19T02:10:57","date_gmt":"2022-03-19T00:10:57","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=11338"},"modified":"2022-04-14T11:46:34","modified_gmt":"2022-04-14T08:46:34","slug":"the-new-basic-realizations-of-operations-equivalence-of-neuro-fuzzy-and-bioinspired-neuro-logics-to-create-hardware-accelerators-of-advanced-equivalental-models-of-neural-structures","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=11338","title":{"rendered":"The new basic realizations of operations \u201cequivalence\u201d of neuro-fuzzy and bioinspired neuro-logics to create hardware accelerators of advanced equivalental models of neural structures and machine vision systems"},"content":{"rendered":"

<\/p>\n

THE NEW BASIC REALIZATIONS OF OPERATIONS \u201cEQUIVALENCE\u201d OF NEURO-FUZZY AND BIOINSPIRED NEURO-LOGICS TO CREATE HARDWARE ACCELERATORS OF ADVANCED EQUIVALENTAL MODELS OF NEURAL STRUCTURES AND MACHINE VISION SYSTEMS<\/p>\n

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\u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 153-166. \u041d\u043e\u043c\u0435\u0440: \u21166, 2021 (303)<\/strong> \"\"<\/a>
\n\u0410\u0432\u0442\u043e\u0440\u0438<\/strong>:<\/p>\n

VLADIMIR KRASILENKO
\nVinnytsia National Agrarian University
\nORCID ID: 0000-0001-6528-3150;
\ne-mail: krasvg@i.ua<\/a>
\nYURCHUK NATALIYA
\nVinnytsia National Agrarian University
\nORCID ID: 0000-0002-7987-9390
\nALEXANDER LAZAREV
\nVinnytsia National Technical University
\nORCID ID: 0000-0003-1176-5650
\ne-mail: alexander.lazarev.vntu@gmail.com
\n\u041a\u0420\u0410\u0421\u0418\u041b\u0415\u041d\u041a\u041e \u0412. \u0413., \u042e\u0420\u0427\u0423\u041a \u041d. \u041f.,
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\n\u041b\u0430\u0437\u0430\u0440\u0454\u0432 \u041e. \u041e.
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\nDOI:<\/strong> https:\/\/www.doi.org\/10.31891\/2307-5732-2021-303-6-153-166<\/a>
\n\u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review : 2<\/strong>0.12.2021 \u0440.
\n\u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430<\/strong>\/<\/strong>Printed<\/strong> :<\/strong> 30.12.2021 \u0440.<\/p>\n

\u0410\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u043c\u043e\u0432\u043e\u044e \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u0443<\/strong><\/p>\n

The perspective of neural networks equivalental models (EM) base on vector-matrix procedure with basic operations of continuous and neuro-fuzzy logic (equivalence, absolute difference) are shown. Capacity on base EMs exceeded the amount of neurons in 4-10 times. This is larger than others neural networks paradigms. Amount neurons of this neural networks on base EMs may be 10 \u2013 100 thousand. The base operations in EMs are normalized equivalence operations. The family of new operations \u201cequivalence\u201d and \u201cnon-equivalence\u201d of neuro-fuzzy logic\u2019s, which we have elaborated on the based of such generalized operations of fuzzy-logic\u2019s as fuzzy negation, t-norm and s-norm are shown. Generalized rules of construction of new functions (operations) \u201cequivalence\u201d which uses operations of t-norm and s-norm to fuzzy negation are proposed. Despite the wide variety of types of operations on fuzzy sets and fuzzy relations and the related variety of new synthesized equivalence operations based on them, it is possible and necessary to select basic operations, taking into account their functional completeness in the corresponding algebras of continuous logic, as well as their most effective circuitry implementations. Among these elements the following should be underlined: 1) the element which fulfills the operation of limited difference; 2) the element which algebraic product (intensifier with controlled coefficient of transmission or multiplier of analog signals); 3) the element which fulfills a sample summarizing (uniting) of signals (including the one during normalizing). The basic element of pixel cells for the construction of hardware accelerators EM NM is a node on the current-reflecting mirrors (CM), which implements the operation of a limited difference (LD) of continuous logic (CL). Synthesized structures which realize on the basic of these elements the whole spectrum of required operations: t-norm, s-norm and new operations \u2013 \u201cequivalence\u201d are shown. These realizations on the basic of CMOS transistors current mirror represent the circuit with analog and time-pulse optical input signals. Possibilities of \u201cequivalence\u201d circuits synthesis by such functions limited difference cells are shown. Such circuits consist of several dozen CMOS transistors, have low power supply voltage (1.8\u20263.3V), the range of an input photocurrent is 0.1\u202624 \u03bcA, the transformation time is less than 1 \u03bcs, low power consumption (microwatts). The circuits and the simulation results of their design with OrCAD are shown.
\nKeywords:<\/strong> self-learning equivalent-convolutional neural structures, equivalent models, continuous-logical operations, hardware accelerator, bioinspired neuro-logic, neuro-fuzzy logic, neuron-equivalentor, current mirror, sorting node, operations \u201cequivalence\u201d and \u201cnon-equivalence\u201d, functional completeness, image processor.<\/p>\n

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\u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f (\u043e\u0431’\u0454\u0434\u043d\u0430\u043d\u043d\u044f) \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432 (\u0443 \u0442\u043e\u043c\u0443 \u0447\u0438\u0441\u043b\u0456 \u043f\u0440\u0438 \u0457\u0445 \u043d\u043e\u0440\u043c\u0430\u043b\u0456\u0437\u0430\u0446\u0456\u0457). \u0411\u0430\u0437\u043e\u0432\u0438\u043c \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u043e\u043c \u043f\u0456\u043a\u0441\u0435\u043b\u044c\u043d\u0438\u0445 \u043a\u043e\u043c\u0456\u0440\u043e\u043a \u0434\u043b\u044f \u043f\u043e\u0431\u0443\u0434\u043e\u0432\u0438 \u0430\u043f\u0430\u0440\u0430\u0442\u043d\u0438\u0445 \u043f\u0440\u0438\u0441\u043a\u043e\u0440\u044e\u0432\u0430\u0447\u0456\u0432 \u0415\u041c \u041d\u041c \u0454 \u0432\u0443\u0437\u043e\u043b \u043d\u0430 \u0432\u0456\u0434-\u0434\u0437\u0435\u0440\u043a\u0430\u043b\u044e\u0432\u0430\u0447\u0430\u0445 \u0441\u0442\u0440\u0443\u043c\u0443 (\u0412\u0414\u0421), \u0449\u043e \u0440\u0435\u0430\u043b\u0456\u0437\u0443\u0454 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u044e \u043e\u0431\u043c\u0435\u0436\u0435\u043d\u043e\u0457 \u0440\u0456\u0437\u043d\u0438\u0446\u0456 \u043d\u0435\u043f\u0435\u0440\u0435\u0440\u0432\u043d\u043e\u0457 \u043b\u043e\u0433\u0456\u043a\u0438. \u041d\u0430 \u043e\u0441\u043d\u043e\u0432\u0456 \u0446\u0438\u0445 \u0431\u0430\u0437\u043e\u0432\u0438\u0445 \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u0456\u0432 \u0441\u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432\u0430\u043d\u0456 \u0442\u0430 \u043d\u0430\u0432\u0435\u0434\u0435\u043d\u0456 \u0431\u0430\u0433\u0430\u0442\u043e\u0444\u0443\u043d\u043a\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0456 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438, \u044f\u043a\u0456 \u0440\u0435\u0430\u043b\u0456\u0437\u0443\u044e\u0442\u044c \u043f\u0440\u0430\u043a\u0442\u0438\u0447\u043d\u043e \u0443\u0432\u0435\u0441\u044c \u0441\u043f\u0435\u043a\u0442\u0440 \u043d\u0435\u043e\u0431\u0445\u0456\u0434\u043d\u0438\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0439: t-\u043d\u043e\u0440\u043c, s-\u043d\u043e\u0440\u043c \u0442\u0430 \u0443\u0441\u0456 \u043d\u043e\u0432\u0456 \u0432\u0438\u0434\u0438 \u0443\u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0435\u043d\u0438\u0445 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0439 \u00ab\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456\u00bb. \u0412\u043e\u043d\u0438 \u0440\u0435\u0430\u043b\u0456\u0437\u043e\u0432\u0430\u043d\u0456 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0456 \u041a\u041c\u041e\u041f-\u0442\u0440\u0430\u043d\u0437\u0438\u0441\u0442\u043e\u0440\u043d\u0438\u0445 \u0432\u0456\u0434\u0434\u0437\u0435\u0440\u043a\u0430\u043b\u044e\u0432\u0430\u0447\u0456\u0432 \u0441\u0442\u0440\u0443\u043c\u0443 \u0442\u0430 \u044f\u0432\u043b\u044f\u044e\u0442\u044c \u0441\u043e\u0431\u043e\u044e \u0441\u0445\u0435\u043c\u0438 \u043d\u0435\u043b\u0456\u043d\u0456\u0439\u043d\u043e\u0457 \u043e\u0431\u0440\u043e\u0431\u043a\u0438 \u0430\u043d\u0430\u043b\u043e\u0433\u043e\u0432\u0438\u0445 \u0447\u0438 \u0447\u0430\u0441\u043e-\u0456\u043c\u043f\u0443\u043b\u044c\u0441\u043d\u043e-\u043a\u043e\u0434\u043e\u0432\u0430\u043d\u0438\u0445 \u0432\u0445\u0456\u0434\u043d\u0438\u0445 \u0441\u0438\u0433\u043d\u0430\u043b\u0456\u0432. \u041f\u043e\u043a\u0430\u0437\u0430\u043d\u043e \u043c\u043e\u0436\u043b\u0438\u0432\u043e\u0441\u0442\u0456 \u0441\u0438\u043d\u0442\u0435\u0437\u0443 \u0441\u0445\u0435\u043c \u00ab\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456\u00bb \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e \u0441\u0443\u043a\u0443\u043f\u043d\u043e\u0441\u0442\u0456 \u0437 \u043f\u043e\u0434\u0456\u0431\u043d\u0438\u0445 \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u0456\u0432, \u0449\u043e \u0440\u0435\u0430\u043b\u0456\u0437\u0443\u044e\u0442\u044c \u043b\u0438\u0448\u0435 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u044e \u043e\u0431\u043c\u0435\u0436\u0435\u043d\u043e\u0457 \u0440\u0456\u0437\u043d\u0438\u0446\u0456. \u0422\u0430\u043a\u0456 \u0441\u0445\u0435\u043c\u0438 \u0441\u043a\u043b\u0430\u0434\u0430\u044e\u0442\u044c\u0441\u044f \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u0445 \u0434\u0435\u0441\u044f\u0442\u043a\u0456\u0432 \u041a\u041c\u041e\u041f-\u0442\u0440\u0430\u043d\u0437\u0438\u0441\u0442\u043e\u0440\u0456\u0432, \u043c\u0430\u044e\u0442\u044c \u043d\u0438\u0437\u044c\u043a\u0443 \u043d\u0430\u043f\u0440\u0443\u0433\u0443 \u0436\u0438\u0432\u043b\u0435\u043d\u043d\u044f (1,8\u20263,3 \u0412), \u0434\u0456\u0430\u043f\u0430\u0437\u043e\u043d \u0432\u0445\u0456\u0434\u043d\u043e\u0433\u043e \u0444\u043e\u0442\u043e\u0441\u0442\u0440\u0443\u043c\u0443 0,1\u202624 \u043c\u043a\u0410, \u0447\u0430\u0441 \u0442\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u0457 \u043c\u0435\u043d\u0448\u0435 1 \u043c\u043a\u0441, \u043d\u0438\u0437\u044c\u043a\u0435 \u0441\u043f\u043e\u0436\u0438\u0432\u0430\u043d\u043d\u044f \u0435\u043b\u0435\u043a\u0442\u0440\u043e\u0435\u043d\u0435\u0440\u0433\u0456\u0457 (\u043c\u0456\u043a\u0440\u043e\u0432\u0430\u0442). \u041d\u0430\u0432\u0435\u0434\u0435\u043d\u0456 \u0441\u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432\u0430\u043d\u0456 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438, \u0441\u0445\u0435\u043c\u0438 \u0457\u0445 \u0431\u0430\u0437\u043e\u0432\u0438\u0445 \u0432\u0443\u0437\u043b\u0456\u0432. \u041f\u043e\u043a\u0430\u0437\u0430\u043d\u0456 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 \u0457\u0445 \u043c\u043e\u0434\u0435\u043b\u044e\u0432\u0430\u043d\u043d\u044f \u0437\u0430 \u0434\u043e\u043f\u043e\u043c\u043e\u0433\u043e\u044e OrCAD. \u0422\u0430\u043a\u0456 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438 \u043c\u0430\u044e\u0442\u044c \u0440\u044f\u0434 \u043f\u0435\u0440\u0435\u0432\u0430\u0433: \u043e\u0434\u043d\u043e\u0440\u0456\u0434\u043d\u0456\u0441\u0442\u044c, \u0432\u0438\u0441\u043e\u043a\u0443 \u0448\u0432\u0438\u0434\u043a\u0456\u0441\u0442\u044c \u0442\u0430 \u043d\u0430\u0434\u0456\u0439\u043d\u0456\u0441\u0442\u044c, \u043f\u0440\u043e\u0441\u0442\u043e\u0442\u0443 \u0441\u0445\u0435\u043c, \u043c\u0430\u043b\u0435 \u0435\u043d\u0435\u0440\u0433\u043e\u0441\u043f\u043e\u0436\u0438\u0432\u0430\u043d\u043d\u044f, \u0432\u0438\u0441\u043e\u043a\u0438\u0439 \u0440\u0456\u0432\u0435\u043d\u044c \u0456\u043d\u0442\u0435\u0433\u0440\u0430\u0446\u0456\u0457 \u0434\u043b\u044f \u043b\u0456\u043d\u0456\u0439\u043d\u0438\u0445 \u0442\u0430 \u043c\u0430\u0442\u0440\u0438\u0447\u043d\u0438\u0445 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440. \u041d\u0430 \u043e\u0441\u043d\u043e\u0432\u0456 \u043d\u0430\u0431\u043e\u0440\u0443 \u0442\u0430\u043a\u0438\u0445 \u0432\u0443\u0437\u043b\u0456\u0432 \u0442\u0430 \u0412\u0414\u0421, \u0440\u0435\u0430\u043b\u0456\u0437\u043e\u0432\u0430\u043d\u0438\u0445 \u0437\u0430 \u041a\u041c\u041e\u041f-\u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0456\u0454\u044e, \u0437\u0430\u043f\u0440\u043e\u043f\u043e\u043d\u043e\u0432\u0430\u043d\u0456 \u0442\u0430 \u0440\u043e\u0437\u0433\u043b\u044f\u043d\u0443\u0442\u0456 \u043c\u0435\u0442\u043e\u0434\u0438 \u043f\u043e\u0431\u0443\u0434\u043e\u0432\u0438 \u0431\u0430\u0437\u043e\u0432\u0438\u0445 \u0435\u043b\u0435\u043c\u0435\u043d\u0442\u0456\u0432-\u043a\u043e\u043c\u0456\u0440\u043e\u043a \u0441\u043a\u0430\u043b\u044f\u0440\u043d\u043e-\u0440\u0435\u043b\u044f\u0446\u0456\u0439\u043d\u0438\u0445 \u0432\u0435\u043a\u0442\u043e\u0440\u043d\u0438\u0445 \u043f\u0440\u043e\u0446\u0435\u0441\u043e\u0440\u0456\u0432 (\u0421\u0420\u0412\u041f) \u0437 \u0444\u0443\u043d\u043a\u0446\u0456\u044f\u043c\u0438 \u00ab\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456\u00bb \u0442\u0430 \u0457\u0445 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440 \u0432 \u0446\u0456\u043b\u043e\u043c\u0443, \u044f\u043a \u043f\u0440\u0438\u0441\u043a\u043e\u0440\u044e\u0432\u0430\u0447\u0456\u0432.
\n\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430:<\/strong> \u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u043e-\u0437\u0433\u043e\u0440\u0442\u043a\u043e\u0432\u0456 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u0456 \u0441\u0442\u0440\u0443\u043a\u0442\u0443\u0440\u0438, \u0449\u043e \u0441\u0430\u043c\u043e\u043d\u0430\u0432\u0447\u0430\u044e\u0442\u044c\u0441\u044f, \u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u0456 \u043c\u043e\u0434\u0435\u043b\u0456, \u0431\u0435\u0437\u043f\u0435\u0440\u0435\u0440\u0432\u043d\u043e-\u043b\u043e\u0433\u0456\u0447\u043d\u0456 \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457, \u0430\u043f\u0430\u0440\u0430\u0442\u043d\u0438\u0439 \u043f\u0440\u0438\u0441\u043a\u043e\u0440\u044e\u0432\u0430\u0447, \u0431\u0456\u043e\u0456\u043d\u0441\u043f\u0456\u0440\u043e\u0432\u0430\u043d\u0430 \u043d\u0435\u0439\u0440\u043e\u043b\u043e\u0433\u0456\u043a\u0430, \u043d\u0435\u0439\u0440\u043e\u043d\u0435\u0447\u0456\u0442\u043a\u0430 \u043b\u043e\u0433\u0456\u043a\u0430, \u043d\u0435\u0439\u0440\u043e\u043d-\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043e\u0440, \u0432\u0456\u0434\u0434\u0437\u0435\u0440\u043a\u0430\u043b\u044e\u0432\u0430\u0447 \u0441\u0442\u0440\u0443\u043c\u0443, \u0432\u0443\u0437\u043e\u043b \u0441\u043e\u0440\u0442\u0443\u0432\u0430\u043d\u043d\u044f, \u043e\u043f\u0435\u0440\u0430\u0446\u0456\u0457 \u00ab\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u0456\u0441\u0442\u044c\u00bb \u0442\u0430 \u00ab\u043d\u0435\u0435\u043a\u0432\u0456\u0432\u0430\u043b\u0435\u043d\u0442\u043d\u0456\u0441\u0442\u044c\u00bb, \u043f\u0440\u043e\u0446\u0435\u0441\u043e\u0440 \u0437\u043e\u0431\u0440\u0430\u0436\u0435\u043d\u043d\u044f, \u043d\u0435\u043b\u0456\u043d\u0456\u0439\u043d\u0430 \u043e\u0431\u0440\u043e\u0431\u043a\u0430, \u0444\u0443\u043d\u043a\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0430 \u043f\u043e\u0432\u043d\u043e\u0442\u0430.<\/p>\n

References<\/strong><\/p>\n

    \n
  1. Zadeh L. A., Fuzzy sets, Inform Control, v.8, pp.338 \u2013 353, 1965.<\/li>\n
  2. Frecman James, Skapura D.M., \u201cNeural Networks: Algorithms applications and programming techniques\u201d, Addison-Wesley Publishing Company, 1992.<\/li>\n
  3. Amosov N.M. et al, \u201cNeurostructures and intelligent robots\u201d, Naukova dumka, Kiev, 1991.<\/li>\n
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