| S# |
Lecture |
Course |
Institute |
Instructor |
Discipline |
| 2026 |
Recitation 8: Poles, Part II (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2027 |
Recitation 2: Inheritance (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2028 |
Recitation 9: Circuits: Representation, KVL, KCL (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2029 |
Recitation 3: Python Notables (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2030 |
Recitation 4: State Machines (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2031 |
Recitation 5: LTI Motivations and Representations (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2032 |
Recitation 6: System Equivalences (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2033 |
Recitation 7: Poles, Part I (M-I-T)
|
Introduction to Electrical Engineering & Computer Science (M-I-T)
|
MIT
|
Dennis Freeman, Kendra Pugh
|
Applied Sciences
|
| 2034 |
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2035 |
11: Spectral Analysis Part 1 (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2036 |
12: Spectral Analysis Part 2 (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2037 |
13: Spectral Analysis Part 3 (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2038 |
14: Rate Models and Perceptrons (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2039 |
15: Matrix Operations (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2040 |
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2041 |
17: Principal Components Analysis (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2042 |
18: Recurrent Networks (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2043 |
19: Neural Integrators (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2044 |
1: Course Overview and Ionic Currents (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2045 |
20: Hopfield Networks (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2046 |
2: Resistor Capacitor Circuit and Nernst Potential (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2047 |
3: Resistor Capacitor Neruon Model (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2048 |
4: Hodgkin-Huxley Model Part 1 (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2049 |
5: Hodgkin-Huxley Model Part 2 (M-I-T)
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
| 2050 |
|
Introduction to Neural Computation (M-I-T)
|
MIT
|
Prof. Michale Fee, Daniel Zysman
|
Applied Sciences
|
