ELEN E6080: Methods of Signal Processing in Computational Neuroscience
Course Benefits
| | • | | Focuses on the intuitive understanding of the theoretical foundations of frames. |
| | • | | Provides a straighforward introduction to spike processing and neural computation. |
| | • | | Enables the further exploration of key concepts at the frontiers of theoretical neuroscience. |
| | • | | Interests in Computational Neuroscience: In Silico: Time Encoding and Information Representation in Sensory Systems, Spike Processing and Computation in the Cortex. In Vivo: Olfactory System of the Drosophila Melanogaster. |
| | • | | Further information about the instructor is available under URL: http://www.ee.columbia.edu/~aurel. |
Applicable Degree Programs
Most courses 4000-level and above can be credited to all degree
programs. All courses are subject to advisor approval.
| Lecturer: |
Professor Aurel A. Lazar |
| |
Office hours: |
Mondays, 2:00 PM - 4:00 PM, EST, Room 819 CEPSR |
| |
E-mail address: |
aurel "at" ee.columbia.edu |
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Class Web Site: |
Offered by CourseWorks |
| Day and Time: |
Fridays, 9:30 AM - 11:30 AM |
| Class Location: |
415 Schapiro (CEPSR) |
| Credits for course: |
3 points |
| Prerequisites |
BMEB W4011 (Computational Neuroscience) or ELEN E4810 (Digital Signal Processing) or the instructor's approval. |
| Description: |
Introduction to Methods and Mathematical Preliminaries. Stimulus Representation with Time Encoding Machines.
Stimulus Recovery with Time Decoding Machines. Information Representation and Frames. Continuous Wavelet and Gabor Transforms.
Discrete Wavelet Transform. Fast Wavelet Transform and Overcomplete Representations. Overcomplete Representations and Multichannel Time Encoding Machines. |
| Required text(s): |
Anthony Teolis, Computational Signal Processing with Wavelets, Birkhauser, Boston, MA, 1998. |
| Homework(s): |
TBA |
| Paper(s): |
--- |
| Project(s) |
One major individual or group project |
| Midterm exam: |
Take-home exam |
| Final Exam: |
Project presentation |
| Grading |
TBA |
| Hardware requirements: |
Laptop for demos |
| Software requirements: |
Matlab (student version) |