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. 2020 Jan 28;20(3):709. doi: 10.3390/s20030709

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© 2020 by the authors.

Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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SIMRR multi-mode sensing based on artificial neuron network. (a) Signal processing model using BP-ANN (back-propagation ANN) for the designed SIMRR multi-mode sensor in the Figure 1a. Influence of the network parameters on its measurement results, (b) MSE (mean squared error) versus number of neurons in the hidden layer, (c) MSE versus learning rate, (d) MSE versus number of training datasets, (e) MSE versus training goal error, (f) Comparison between the estimated values of the length change and their corresponding theoretical values.