Modular machine learning based circuit design
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Systems, control and mechatronics (MPSYS), MSc
Publicerad
2024
Författare
Ekarna, Jacob
Lind, Erik
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
In traditional circuit design a pre-selected circuit topology is optimized through time
consuming parameter sweeps to satisfy a design criteria. A newly introduced design
concept instead utilizes machine learning models to predict the transfer function
of a given circuit structure, together with a genetic algorithm to generate a circuit
based on wanted scattering parameters.
The concept of machine learning in circuit design, however, has its drawbacks. One
notable drawback is that the circuits generated from the model are all of the same
size the model was trained on, leading to scalability issues. To overcome this problem
this thesis evaluated whether or not it is possible to use a machine learning model
trained on a dataset of smaller 9 × 9 circuits to create a larger modular circuit, consisting of four modules. The generated modular circuits were assessed by comparing
the predicted scattering parameters from the optimization to the pre-selected target
parameters. Additionally, simulations were performed on the generated circuits and
the results were compared with the predicted parameters. The thesis also investigated if the implementation of a via fence could help isolate the modules from
eachother to reduce electromagnetic interference and improve performance. The
differences in time efficiency between the two cases were also compared.
The results show that the modular concept works to a high degree. Based on
simulation results, the root mean square error for the scattering parameters for
the non-via fence model was 0.05934 and for the via fence model it was 0.04677.
Adding a via fence improves the model predictions slightly and further improves
the simulated circuits significantly. The results for the circuit designs with a via
fence, over 100 generated circuits designs, were 13 % more accurate than the circuit
designs without a via fence. However, this came at the cost of increased simulation
time, as circuits using a via fence took a considerably longer time to simulate.
Beskrivning
Ämne/nyckelord
Circuit design, Modular, Scattering parameters, Machine Learning, Genetic Algorithm