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- W2053641344 abstract "Genetic algorithms in active noise control (ANC) eliminates the need to know the cancellation path, necessary for a conventional gradient descent-type algorithm (such as filtered-x and filtered-U) to remain stable. However, genetic algorithms show some disadvantages: slow convergence, high residual error noise, and high computational complexity. This paper presents a simple genetic algorithm that improves these quality factors, simplifying the basic stages of the genetic algorithm: population size, selection, reproduction, and mutation. To reduce the algorithm computation the population size is low, 6 chromosomes (filter coefficients) maximum, and only the best chromosome is selected so the reproduction stage disappears. Next generation of chromosomes is generated mutating the selected chromosome with a variable random number which amplitude is directly proportional to the mean-squared error in the current generation. This variable mutation is the most important parameter because it determines the stability, the convergence, and the final residual level. Good results have been obtained for narrow-band signals in single (SISO) and multiple (MIMO) ANC configurations and with FIR or IIR filters. These results shows fast convergence, only four or five generations are necessary with very reduced populations (6 chromosomes in SISO systems and 2 to 3 chromosomes in MIMO systems) and an attenuation better than 20 dB." @default.
- W2053641344 created "2016-06-24" @default.
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- W2053641344 date "1998-05-01" @default.
- W2053641344 modified "2023-10-03" @default.
- W2053641344 title "A simple genetic algorithm for active noise control" @default.
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- W2053641344 doi "https://doi.org/10.1121/1.422253" @default.
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