Abstract
This paper presents the Gene Fragment Competition concept that can be used with Hybrid Genetic Algorithms specially in signal and image processing. Memetic Algorithms have shown great success in real-life problems by adding local search operators to improve the quality of the already achieved “good” solutions during the evolutionary process. Nevertheless these traditional local search operators don’t perform well in highly demanding evaluation processes. This stresses the need for a new semi-local non-exhaustive method. Our proposed approach sits as a tradeoff between classical Genetic Algorithms and traditional Memetic Algorithms, performing a quasi-global/quasi-local search by means of gene fragment evaluation and selection. The applicability of this hybrid Genetic Algorithm to the signal processing problem of Polyphonic Music Transcription is shown. The results obtained show the feasibility of the approach.
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Reis, G., Fonseca, N., Fernández de Vega, F., Ferreira, A. (2008). Hybrid Genetic Algorithm Based on Gene Fragment Competition for Polyphonic Music Transcription. In: Giacobini, M., et al. Applications of Evolutionary Computing. EvoWorkshops 2008. Lecture Notes in Computer Science, vol 4974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78761-7_31
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DOI: https://doi.org/10.1007/978-3-540-78761-7_31
Publisher Name: Springer, Berlin, Heidelberg
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