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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 Yang
Presenter: Yu-Kai Wang
Advisor: Dr. Yeou-Jiunn Chen
Date: 2013.3.6
Outline
Introduction
Purposes
Materials and Methods
Results
Conclusions
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
Material and Methods
 The selected wavelets had almost the same frequency at a 0dB 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
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