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- W3020042600 abstract "In the new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm." @default.
- W3020042600 created "2020-05-01" @default.
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- W3020042600 creator A5017610833 @default.
- W3020042600 date "2018-01-01" @default.
- W3020042600 modified "2023-09-27" @default.
- W3020042600 title "Intelligent Technique to Identify Epilepsy Using Fuzzy Firefly System for Brain Signal Processing" @default.
- W3020042600 cites W1991359419 @default.
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- W3020042600 doi "https://doi.org/10.4018/978-1-5225-2857-9.ch020" @default.
- W3020042600 hasPublicationYear "2018" @default.
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