مشاهده مشخصات مقاله
Improving EEG Signal Prediction via SSA and Channel Selection
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نویسنده (ها) |
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Bahareh Atoufi
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Ali Zakerolhosseini
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Caro Lucas
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
Being able to predict the coming seizure can
impressively improve the quality of the patients' lives
since they can be warned to avoid doing risky activities
via a prediction system. Here, a locally linear neuro
fuzzy model is used to predict the EEG time series.
Subsequently, this model is utilized in accompany with
Singular Spectrum Analysis for prediction. Afterward,
an information theoretic criterion is used to select a
reliable subset of input variables which contain more
information about the target signal. Comparison of
three mentioned methods on one hand shows that SSA
enables our prediction model to extract the main
patterns of the EEG signal and highly improves the
prediction accuracy. On the other hand, applying the
method of channel selection to the model yields more
accurate prediction. It is shown that fusion of some
certain signals provides more information about the
target and considerably improves the prediction
ability. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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خرید مقاله
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