1 / 5

Advanced Numeric Methods in EEG and Signal Processing: CSE 291 Spring 2014

This course, CSE 291, focuses on advanced numeric methods applied to signal processing, particularly in the analysis of EEG data. Instructed by Chung-Kuan Cheng, students will explore topics including the theorem of signal averaging, data analysis techniques (like Hilbert-Huang transform and digital signal filtering), source analysis (PCA and ICA), network analysis (Granger causality and brain connectivity), and system modeling (nonlinear dynamics). Assignments will involve hands-on projects analyzing EEG, MEG, or ECG data, alongside methods construction.

ranee
Télécharger la présentation

Advanced Numeric Methods in EEG and Signal Processing: CSE 291 Spring 2014

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CSE291 Topics on Numeric Methods Spring 2014 Time and Place: 5-620PM, WF, Room CSE2109 Instructor: Chung-Kuan Cheng

  2. Theorem of Signal Averaging “Backgroud” EEG

  3. Event-related (De-)Synchronization • Time- but NOT phase-lock signals • Highly frequency-specific • ERD/ERS are location-dependent Figure is from Pfurtschellera & Lopes da Silvab, Clinical Neurophys., 1999.

  4. Contents • 1. Data analysis: • 1.1 Hilbert-Huang transform, • scalar and multiple dimensional function extraction • 1.2 Filters: Digital Signal Processing • 1.3 Wavelet • 2. Source Analysis: • 2.1 PCA, ICA, Vestal • 2.2 Compressed sensing • 2.3 Forward and inverse problems • 2.4 Spike sorting • 3. Network Analysis • 3.1 Granger causality • 3.2 Coherence • 3.3 Brain connectivity • 4. System Modeling • 4.1 Nonlinear dynamic systems • 4.2 Entropy and phase diagram • 4.3 Augmentation index

  5. Assignment • Projects • Analyze EEC, MEG, or ECG data or • Construct analysis methods • Report • Survey <= 4pages • Presentation <= 30 min

More Related