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 3 shows
 The magnitudes of frequency responses of WLD for 110
wavelets
Decomposed into seven levels
reconstruction
Material and Methods
 For the filter, the stop band can be defined to be at the
frequency whose gain is below -20 dB
 In order to separate the responses of repeated stimuli and the
MMN
 The stop frequency should be around 8.5 Hz

This is the first criterion for choosing a suitable wavelet
Material and Methods
 Figure 4 shows
 The frequency responses with gains of -20 dB and 0 dB
for each wavelet, respectively
24 wavelets were chosen, all had
a 0-dB gain at around 2 Hz