Design and simulation of cells, that realize arbitrary functions of activations of neurons in self-learning equivalent-convolutional neural structures
Автор
Krasilenko, V. G.
Lazarev, A. A.
Nikitovich, D. V.
Красиленко, В. Г.
Лазарєв, О. О.
Нікітович, Д. В.
Дата
2018Metadata
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- Наукові роботи каф. ІКСТ [422]
Аннотации
We consider the urgent need to create hardware
accelerators for CNN. We show a overview of the equivalent models
(EMs), EM-paradigms for recognition images and learning with CL-
operations as: "equivalence". We consider approaches to the design
of arrays of neuron-equivalentors (NEs) with different activation
functions. Approach is based on the use of mixed methods, building
NEs (with number of synapsis 128) and their cells based current
mirrors. Simulations show that the efficiency of NEs relative to the
energy is estimated at a value of not less 10^12 an. op. / sec on W.
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http://ir.lib.vntu.edu.ua//handle/123456789/23589