| Autors: Ivanova, M. S., Durcheva, M. I. Title: M-Polar Fuzzy Graphs and Deep Learning for the Design of Analog Amplifiers Keywords: analog amplifier; automation; deep learning; design process; Abstract: The design of analog circuits is a complex and repetitive process aimed at finding the best design variant. It is characterized by uncertainty and multivariate approaches. The designer has to make different choices to satisfy a predefined specification with required parameters. This paper proposes a method for facilitating the design of analog amplifiers based on m-polar fuzzy graphs theory and deep learning. M-polar fuzzy graphs are used because of their flexibility and the possibility to model different real-life multi-attribute problems. Deep learning is applied to solve a regression task and to predict the membership functions of the m-polar fuzzy graph vertices (the solutions), taking on the role of domain experts. The performance of the learner is high since the obtained errors are very small. The proposed method is verified through the design of of three amplifiers. References Issue
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