Sponsor
Portland State University. Department of Electrical Engineering
First Advisor
Fu Li
Date of Publication
11-19-1993
Document Type
Thesis
Degree Name
Master of Science (M.S.) in Electrical Engineering
Department
Electrical Engineering
Language
English
Subjects
Wavelets (Mathematics), Pattern perception, Evoked potentials (Electrophysiology)
DOI
10.15760/etd.6507
Physical Description
1 online resource (2, viii, 56 p.)
Abstract
Wavelet transform provides an alternative to the classical Short-Time Fourier Transform (STFT). In contrast to the STFT, which uses a single analysis window, the Wavelet Transform uses shorter windows at higher frequencies and longer windows at lower frequencies. For some particular wavelet functions, the local maxima of the wavelet transform correspond to the sharp variation points of the signal. As an application, wavelet transform is introduced to the character recognition. Local maximum of wavelet transform is used as a local feature to describe character boundary. The wavelet method performs well in the presence of noise. The maximum of wavelet transform is also an important feature for analyzing the properties of brain wave. In our study, we found the maximum of wavelet transform was related to the P300 latency. It provides an easy and efficient way to measure P300 latency.
Rights
In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Persistent Identifier
https://archives.pdx.edu/ds/psu/26722
Recommended Citation
Qi, Hong, "Pattern Recognition and ERP Waveform Analysis Using Wavelet Transform" (1993). Dissertations and Theses. Paper 4623.
https://doi.org/10.15760/etd.6507
Comments
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