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 ,China
Department of Psychology,University of Jyväskylä, Jyväskylä 40014,Finland
Received 6 Apr 2011; Accepted 14 Sep 2011; doi: /jmbe.908
Chairman:Hung-Chi Yang Presenter: Yu-Kai Wang
Advisor: Dr. Yeou-Jiunn Chen Date:

2. Outline
Introduction
Purposes
Materials and Methods
Results
Conclusions

3. Material and Methods Figure 5 shows
The gains of the frequency responses at 8.5 Hz and 0.1 Hz for each wavelet
The wavelet gain at 8.5 Hz should be below -20 dB

4. Material and Methods
The selected wavelets had almost the same frequency at a 0-dB gain
The gain of the frequency responses at 0.1 Hz should be as low as possible to remove low-frequency drift
To make the final decision, the frequency responses of WLD for the two wavelets were calculated, respectively

5. Material and Methods Figure 6 shows
The magnitudes of their frequency responses and that for the ODF
Daubechies wavelet with an order of 7 between 8.8 Hz and 10.8 Hz were larger than -20dB, so this wavelet was rejected
The reverse biorthogonal wavelet with an order of 6.8 was chosen for the WLD of MMN