Wyniki wyszukiwania - BazTech

1

Predictive neural network in multipurpose self-tuning controller

Bondar Oleksiy

Acta Mechanica et Automatica

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2020

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Vol. 14, no. 2

114--120

EN

A very important problem in designing of controlling systems is to choose the right type of architecture of controller. And it is always a compromise between accuracy, difficulty in setting up, technical complexity and cost, expandability, flexibility and so on. In this paper, multipurpose adaptive controller with implementation of artificial neural network is offered as an answer to a wide range of tasks related to regulation. The effectiveness of the approach is demonstrated by the example of an adaptive thermostat. It also compares its capabilities with those of classic PID controller. The core of this approach is the use of an artificial neural network capable of predicting the behaviour of controlled object within its known range of parameters. Since such a network, being trained, is a model of a regulated system with arbitrary precision, it can be analysed to make optimal management decisions at the moment or in a number of steps. Network learning algorithm is backpropagation and its modified version is used to analyse an already trained network in order to find the optimal solution for the regulator. Software implementation, such as graphical user interface, routines related to neural network and many other, is done using Java programming language and Processing open-source integrated development environment.

2

Effectiveness comparison on an artificial neural networks to identify Polish emotional speech

Powroźnik P., Czerwiński D.

Przegląd Elektrotechniczny

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2016

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R. 92, nr 7

45--48

EN

This article presents the issue of Polish emotional speech recognition based on Polish database prepared by Medical Electronic Division of the Lodz University of Technology. The main goal of this article was to show the differences is artificial neuron networks learning processes. Researches were conducted on the basis of the five most popular variants of the back propagation algorithm. The neuron activation function was the second analyzed issue.

PL

Artykuł prezentuje możliwe zastosowanie sztucznych sieci neuronowych do identyfikacji stanów emocjonalnych mówcy. Badania zostały przeprowadzone w oparciu o pięć najpopularniejszych wariantów algorytmu wstecznej propagacji błędów. W badaniach wykorzystano polska bazę mowy emocjonalnej przygotowaną przez Zakład elektroniki Medycznej Politechniki Łódzkiej.

3

Zastosowanie głębokich sieci neuronowych do ekstrakcji semantycznie znaczących znaków

Adamovich-Golovko V., Aliaksandrovich-Kroshchanka A.

Studia i Materiały / Europejska Uczelnia Informatyczno-Ekonomiczna w Warszawie

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2014

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Nr 2(8)

123--135

PL

W pracy przedstawiono podstawowe zasady budowy i nauczania sieci neuronowej głebokiego zaufania do określenia semantycznie ważnych oznak na podstawie próbki CIFAR-10. Dla przygotowania do nauki sieci neuronowej głębokiego zaufania stosuje się opracowane podejście na podstawie minimalizacji błędu rekonstrukcyjnego obrazów widocznych i ukrytych dla ograniczonej maszyny Boltzmanna (RBM).

EN

The main principles of construction and learning deep belief neural networks for extraction valuable semantic features are proposed. The proposed approach is based on minimization of reconstruction mean square error, which we can obtain using a simple iterations of Gibbs sampling.