Digital Filter Design via Recurrent Cartesian Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7656

@InProceedings{Ly:2023:IWCIA,

• author = "Edward Ly and Julian Villegas",
• booktitle = "2023 IEEE 13th International Workshop on Computational Intelligence and Applications (IWCIA)",
• title = "Digital Filter Design via Recurrent Cartesian Genetic Programming",
• year = "2023",
• pages = "7--12",
• abstract = "We introduce a method for the automatic program induction of Single-Input/Single-Output (SISO) Infinite Impulse Response (IIR) filters for Digital Signal Processing (DSP) applications. Recurrent Cartesian Genetic Programming (RCGP) evolves a population of DSP programs, represented as directed cyclic/acyclic graphs, to generate a filter whose magnitude response approximates that of a target filter. The Log-Spectral Distance (LSD) is used as a fitness measure to minimise the differences between the magnitude responses of these filters, and the filter with the smallest distance is output. We evaluated our method by generating a number of filters, and found that the accuracy of the generated filters depends on both the order of the target filter and the parameter values set for the RCGP algorithm.",
• keywords = "genetic algorithms, genetic programming, Cartesian genetic programming, Finite impulse response filters, Software algorithms, Sociology, Signal processing algorithms, IIR filters, Digital signal processing, Digital signal processing, Evolutionary algorithms, Filter design",
• DOI = "doi:10.1109/IWCIA59471.2023.10335891",
• ISSN = "1883-3977",
• month = nov,
• notes = "Also known as \cite{10335891}",

}

Genetic Programming entries for Edward Ly Julian Villegas

Citations