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Chairman:Hung -Chi Yang Presenter: Yu-Kai Wang Advisor: Dr. Yeou-Jiunn Chen Date: 2013.3.6

Frequency-response-based Wavelet Decomposition for Extracting Children’s Mismatch Negativity Elicited by Uninterrupted Sound. Department of Mathematical Information Technology ,University of Jyväskylä,Jyväskylä 40014,Finland

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Chairman:Hung -Chi Yang Presenter: Yu-Kai Wang Advisor: Dr. Yeou-Jiunn Chen Date: 2013.3.6

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  1. Frequency-response-based Wavelet Decomposition for Extracting Children’s Mismatch Negativity Elicited by Uninterrupted Sound Department of Mathematical Information Technology ,University of Jyväskylä,Jyväskylä 40014,Finland Center for Intelligent Maintenance Systems,University of Cincinnati,OH 45221,USA School of Psychology, Beijing Normal University,Beijing 100875,China Department of Psychology,University of Jyväskylä, Jyväskylä 40014,Finland Received 6 Apr 2011; Accepted 14 Sep 2011; doi: 10.5405/jmbe.908 Chairman:Hung-Chi YangPresenter: Yu-Kai Wang Advisor: Dr. Yeou-Jiunn ChenDate: 2013.3.6

  2. Outline • Introduction • Purposes • Materials and Methods • Results • Conclusions

  3. Material and Methods • Figure 2 shows • The frequency ranges of the levels are different from those given in Table 1 • The magnitude responses are not as flat as those obtained using an optimal band-pass digital filter • The fifth and sixth levels are the optimal levels for reconstructing MMN

  4. Material and Methods the optimal levels

  5. Material and Methods • The next step is to determine which wavelet is the most appropriate for evaluating MMN • The wavelet toolbox of MATLAB 7.1, used here for data processing • Daubechies wavelets • Coiflets • symlets • Discrete Meyer wavelets • Biorthogonal wavelets • Reverse biorthogonal wavelets

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