Loudspeaker filter optimization with AI
Electrical circuit representation, mutation and analysis for AI
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Abstract
This paper reports the design of a part of a genetic algorithm, which is made to design analog filters for loudspeakers. The part in this report is the part which deals with the representation of electrical filter circuits, the mutation of these filters, and finding their transfer function. The considered representations are graph coding and a tree data structure. They are compared on intuitiveness, how well mutations can be performed, and the complexity of calculating the transfer function. The tree structure is reasoned to be the most suitable. Described is which mutations can be performed on a filter by the final program, as well as how embryo circuits are made, how the transfer function is calculated, and which hyperparameters were designed and how they were set. Finally, the design is implemented using Python and the operations are tested.