CSE 291 Topics on Numeric Methods for Biosignal Processing Spring 2014

University of California, San Diego

Course Information

Instructor

• CK Cheng, ckcheng+291@ucsd.edu, 858 534-6184

Schedule

• Lectures: 5:00-6:20PM, WF, Room CSE2109

References

• The Computational Brain by P.S. Churchland and T.J. Sejnowski, MIT Press, 1992, and a collection of recent publications.

Content In this course, we discuss the following subjects.

• 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

Lecture Notes and Papers

• Lecture 1: Introduction
• The explosion of data and sensors by J. Bryzek
• Letcture 2: Time Series Data
• Examples of time series data: Speech tuning of neurons, by Chan, et al., and the Slides of Speech tuning.
• Hilbert Huang Transfrom,
• Letcture 3: Nonlinear Dynamic Systems
• Ergodic Measures by A. Mandell,
• Letcture 4: Time Series Data
• Time Series by Y.H. Hu,
• Multivariate EMD by J. Zhao,
• Multivariate EMD by N. Huang ,
• Letcture 5: Source Analysis
• Independent Component Analysis by T.P. Jung,
• Articles: Vestal by M. Huang, and Fast Vestal by M. Huang.
• PCA slides by B. Poczos