Application of Neutral Network by EEG Signal Classification
Analysis of long-term EEG requires that it is segmented into piece-wise stationary sections and classified. Neural network architecture is introduced for the problem of classification of EEG signals. This paper deals with basic signal classification into two classes. This work is a ground towards cr...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
VSB-Technical University of Ostrava
2008-01-01
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| Series: | Advances in Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://advances.utc.sk/index.php/AEEE/article/view/136 |
| _version_ | 1827947724611256320 |
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| author | Michal Gala Jitka Mohylova Vladimir Krajca |
| author_facet | Michal Gala Jitka Mohylova Vladimir Krajca |
| author_sort | Michal Gala |
| collection | DOAJ |
| description | Analysis of long-term EEG requires that it is segmented into piece-wise stationary sections and classified. Neural network architecture is introduced for the problem of classification of EEG signals. This paper deals with basic signal classification into two classes. This work is a ground towards creating an algorithm to sleep status analysis. Signal is first worked by signal segmentation and then is used a neural network to classification into two class. |
| first_indexed | 2024-04-09T12:44:22Z |
| format | Article |
| id | doaj.art-97c075bceaa94279978dea7a07ad1503 |
| institution | Directory Open Access Journal |
| issn | 1336-1376 1804-3119 |
| language | English |
| last_indexed | 2024-04-09T12:44:22Z |
| publishDate | 2008-01-01 |
| publisher | VSB-Technical University of Ostrava |
| record_format | Article |
| series | Advances in Electrical and Electronic Engineering |
| spelling | doaj.art-97c075bceaa94279978dea7a07ad15032023-05-14T20:50:04ZengVSB-Technical University of OstravaAdvances in Electrical and Electronic Engineering1336-13761804-31192008-01-0171 - 234634999Application of Neutral Network by EEG Signal ClassificationMichal Gala0Jitka Mohylova1Vladimir Krajca2VSB - Technical University of OstravaVSB - Technical University of OstravaVSB - Technical University of OstravaAnalysis of long-term EEG requires that it is segmented into piece-wise stationary sections and classified. Neural network architecture is introduced for the problem of classification of EEG signals. This paper deals with basic signal classification into two classes. This work is a ground towards creating an algorithm to sleep status analysis. Signal is first worked by signal segmentation and then is used a neural network to classification into two class.http://advances.utc.sk/index.php/AEEE/article/view/136long-term eegneural networkeeg signal. |
| spellingShingle | Michal Gala Jitka Mohylova Vladimir Krajca Application of Neutral Network by EEG Signal Classification Advances in Electrical and Electronic Engineering long-term eeg neural network eeg signal. |
| title | Application of Neutral Network by EEG Signal Classification |
| title_full | Application of Neutral Network by EEG Signal Classification |
| title_fullStr | Application of Neutral Network by EEG Signal Classification |
| title_full_unstemmed | Application of Neutral Network by EEG Signal Classification |
| title_short | Application of Neutral Network by EEG Signal Classification |
| title_sort | application of neutral network by eeg signal classification |
| topic | long-term eeg neural network eeg signal. |
| url | http://advances.utc.sk/index.php/AEEE/article/view/136 |
| work_keys_str_mv | AT michalgala applicationofneutralnetworkbyeegsignalclassification AT jitkamohylova applicationofneutralnetworkbyeegsignalclassification AT vladimirkrajca applicationofneutralnetworkbyeegsignalclassification |