2017 2nd International Ural Conference on Measurements (UralCon) 2017
DOI: 10.1109/uralcon.2017.8120743
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Dynamic measurement error correction on the basis of recurrent neural network

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“…This model is represented as the sequential connection of the correcting filter and identical first-order sections [14]. Every such section is the ANN inverse model of a first-order LTI system with the following TF:…”
Section: Sequential Representationmentioning
confidence: 99%
“…This model is represented as the sequential connection of the correcting filter and identical first-order sections [14]. Every such section is the ANN inverse model of a first-order LTI system with the following TF:…”
Section: Sequential Representationmentioning
confidence: 99%