• Neural Engineering
• Syllabus
• Lecture 01
• Lecture 02
• Lecture 03
• Lecture 04: A Single Neuron
• Lecture 05: Diff Eqs and Networked Neurons
• Matlab Tutorial
• Lecture 06: MEA
• Lecture 07
• Lecture 08: MEA Signal Analysis
• Lecture 09: Spike Sorting
• Lecture 10: PCA
• Lecture 11: K-means
• Spike Data
• Lecture 12
• Lecture 13
• Lecture 14
• Ch. 13 Project Data
• Ch. 17 Project Data
• Lecture 15: Decoding (ppt)
• Lecture 16: Continuous Decoding (handout)
• Lecture 17: BCI Intro.
• Lecture 18: BCI 1
• Lecture 19: BCI 2
• Lecture 20
• Lecture 21-25
• Lecture 26

• Neural Physiology
• Syllabus
• Lecture 00 Intro to NP
• Lecture 01: Action Potentials
• Lecture 02: Cell Membrane
• Lecture 03: CNS I
• Lecture 04: CNS II
• Lecture 05: Sensory Receptors
• Lecture 06: Somatic Sensations
• Lecture 07: Pain
• Lecture 08
• Lecture 09
• Lecture 10
• Lecture 11
• Lecture 12 Ear
• Lecture 13
• Lecture 14 Smell Supplementary
• Lecture 15
• Lecture 16
• Lecture 17
• Lecture 18

• Homework 01 (Ch. 5)
• Homework 02
• Homework 03
• Homework 04
• Homework 05

• Pattern Recognition
• Syllabus
• Textbook
• Lecture 01
• Lecture 02
• Lecture 03
• Lecture 04
• Lecture 05: Perceptron Example
• Lecture 06
• Lecture 07
• Lecture 08
• Lecture 09
• Lecture 10
• Lecture 11
• Lecture 12
• Lecture 13
• Lecture 14
• Lecture 15
• Lecture 16
• Lecture 17
• Lecture 18
• Lecture 19 Intro to Hier Clustering
• Lecture 20 K-mean function K-means
• Gau. Mixture Paper
• Lecture 21 (PCA) Tutorial of PCA
• Lecture 22 (ICA) What is ICA ICA for Biomedical ICA for Multimedia

• Homework #1 Solutions
• Homework #2 Solutions
• Homework #3 Solutions
• Homework #4 Solutions
• MidTerm
• Homework #5 Solutions
• Homework #6 Solutions