USING NEURAL NETWORKS FOR ERROR SUPPRESSION IN NONLINEAR SYSTEMS WITH HYSTERESIS
Journal Title: Metrology and Measurement Systems - Year 2006, Vol 13, Issue 1
Abstract
Some shortcomings of nonlinear systems with hysteresis are relatively big errors, e.g. linearity error, hysteresis error, etc. The paper deals with possible improvements in the methods of error suppression by using neural networks. Another aim of the paper is evaluation of measurement uncertainty. It reviews the procedures currently applied for measurement uncertainty calculation according to ISO Guide.
Authors and Affiliations
JOZEF VOJTKO
Keywords
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