Tensor products algebra applied to time frequency analysis of auditory encephalographic signal

dc.contributor.advisor Manian, Vidya Aceros-Moreno, Cesar A. College of Engineering en_US
dc.contributor.committee Rodriguez, Domingo
dc.contributor.committee Rodriguez, Nestor
dc.contributor.committee Vega-Riveros, Jose Fernando
dc.contributor.department Department of Electrical and Computer Engineering en_US
dc.contributor.representative Baiges-Valentin, Ivan 2019-06-04T13:45:57Z 2019-06-04T13:45:57Z 2019-05-15
dc.description.abstract Time-frequency methods (TFM) increase the dimensionality of signal spaces. In this thesis, a computational signal processing framework using tensor products algebra is developed to map Electroencephalographic (EEG) signals to time-frequency space, extract robust features and classify them. EEG signal acquisition is a modality to record brain signals using electrodes placed on the scalp of a subject. The signals are recorded with 32 electrodes while the subject listens to an auditory stimulus such as repeated tones, vowels, or words. The TFM used are cyclic short time Fourier transform (CSTFT) and continuous wavelet transform (CWT). The framework takes as input the raw EEG signals. The time-frequency sparse representations using the STFT and CWT are computed on the noise free channels at di erent time steps. The source localization using event related potentials (ERP) can be compared with time-frequency based localization. Results of multichannel EEG nonnegative matrix factorization (NMF) and reconstruction is also presented. The algorithms are implemented as part of a multichannel signal analysis toolbox (MSAT) using the Python programming language. The algorithms presented in this thesis can be extended to more general algorithms for analyzing and classifying the sources of multichannel biosensory signals. en_US
dc.description.graduationSemester Spring en_US
dc.description.graduationYear 2019 en_US
dc.language.iso en en_US
dc.rights.holder (c) 2019 Cesar A. Aceros Moreno en_US
dc.rights.license All rights reserved
dc.subject Time-frequency Methods en_US
dc.subject Electroencephalography en_US
dc.subject Cyclic Short Time Fourier Transform en_US
dc.subject Continuous Wavelet Transform en_US
dc.subject Computational Signal Processing Framework en_US
dc.subject.lcsh Signal processing -- Mathematics en_US
dc.subject.lcsh Tensor products en_US
dc.subject.lcsh Electroencephalography en_US
dc.subject.lcsh Fourier transformation en_US
dc.subject.lcsh Wavelets (Mathematics) en_US
dc.subject.lcsh Algorithms en_US
dc.title Tensor products algebra applied to time frequency analysis of auditory encephalographic signal en_US
dc.type Dissertation en_US
dspace.entity.type Publication Electrical Engineering en_US Ph.D. en_US
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