Abstract
The monotonous and frequent complication in the estimation of dielectric constant expressed interns of frequency in microwave range by incorporating Artificial Neural Networks (ANN). This computerized modus operandi is dependent on the deployment of a slotted line to take measurement which requires a numeric elucidation to resolve the dielectric constant. Automation of the dielectric constant is carried out by developing a computer program for gathering the data acquisition from the conventional setup and modernizing the same using ANN is described here. Investigational data gathered by this existing apparatus is used for training and testing the ANN trained with Back Propagation Algorithm (BPA). An equation formerly obtained from the literature, is used for estimating the dielectric constant. This is compared as an additional function with the computerized algorithm for calibration purpose. Thus, a novel ANN-based scheme for outlining the disparities between various dielectric materials to approximate the dielectric constant is experimentally analyzed using MATLAB.
K. Sujatha—Masterminded EasyChair and created the first stable version of this document.
Nallamilli P. G. Bhavani—Created the first draft of this document.
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Sujatha, K., Ponmagal, R.S., Saravanan, G., Bhavani, N.P.G. (2019). Estimation of Microwave Dielectric Constant Using Artificial Neural Networks. In: Rathore, V., Worring, M., Mishra, D., Joshi, A., Maheshwari, S. (eds) Emerging Trends in Expert Applications and Security. Advances in Intelligent Systems and Computing, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-2285-3_5
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DOI: https://doi.org/10.1007/978-981-13-2285-3_5
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