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Author Takahashi, K.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2012
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Training ♦ parallel controller ♦ Quantum computing ♦ qubit neuron ♦ Neurons ♦ Control systems ♦ Cost function ♦ servo control ♦ Biological neural networks ♦ quantum neural network
Abstract This paper presents an adaptive-type parallel controller based on a quantum neural network and investigates its characteristics for control systems. A multi-layer quantum neural network that uses qubit neurons as an information processing unit is utilized to design the adaptive-type parallel controller that conducts the training of the quantum neural network as an online process. Computational experiments to control the single-input single-output nonlinear discrete time plant are conducted in order to evaluate the learning performance and capability of the adaptive-type quantum neural parallel controller. The results of the computational experiments confirm both the feasibility and the effectiveness of the adaptive-type quantum neural parallel controller.
Description Author affiliation: Information Systems Design, Faculty of Science and Engineering, Doshisha University, Kyoto, Japan (Takahashi, K.)
ISBN 9781467351171
ISSN 21647143
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2012-11-27
Publisher Place India
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781467351195
Size (in Bytes) 295.31 kB
Page Count 5
Starting Page 871
Ending Page 875


Source: IEEE Xplore Digital Library