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• W2742011883 abstract "This paper proposes a methodology based on computational statistics to estimate the states and reconstruct signals from a electroencephalogram (EEG). The results show that the filters in parallel reconstruct well the states of the electrodes independently. The FKEn and FKSES very good shape reconstruct the EEG signal from the independent electrodes. Two measurements to study the e ectiveness of parallelized algorithm, specifically the acceleration and e ciency for a di erent number of threads (pthreads) were calculated. Was obtained for a value P = 2 threads acceleration and e ciency ideal indicate increased speed with respect to the algorithm sequentially. Additionally, the mean absolute error of the states subsequently as a measure of goodness of fit was estimated, showing little variation between the estimated errors. In relation to the execution times of the algorithms significant di erence between the filters it was obtained, the most e cient and the FKEn FKSES FKE." @default.
• W2742011883 created "2017-08-08" @default.
• W2742011883 creator A5045050319 @default.
• W2742011883 creator A5089818505 @default.
• W2742011883 date "2015-01-01" @default.
• W2742011883 modified "2023-09-27" @default.
• W2742011883 title "Parallelized algorithms to reconstruct a electroencephalogram signal" @default.
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• W2742011883 hasPublicationYear "2015" @default.
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