Parameter Estimation of Combinational Circuits Using Machine Learning Methods

Student: Artur Ziazetdinov

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Information Science and Computation Technology (Bachelor)

Year of Graduation: 2024

In modern conditions, the development of microelectronics places high demands on the design processes of electronic components. The efficiency and speed of analyzing the characteristics of combinational circuits are key factors in this process. The thesis presents a new approach to estimating their parameters using machine learning methods, which opens wide opportunities for optimizing the design process. As a result of this work, a dataset of combinational circuits was generated, software for its systematization and normalization was developed. Also, architectures of neural network models were developed, software for automation of hyperparameter search was realized, training, validation and testing of models with subsequent recording of predictions in the form of CSV tables was carried out.

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