6.01SC Introduction to Electrical Engineering and Computer Science I
6.01SC Introduction to Electrical Engineering and Computer Science I (Spring 2011, MIT OCW). Taught by Professor Dennis Freeman, this course provides an integrated introduction to electrical engineering and computer science, taught using substantial laboratory experiments with mobile robots. Our primary goal is for you to learn to appreciate and use the fundamental design principles of modularity and abstraction in a variety of contexts from electrical engineering and computer science. Our second goal is to show you that making mathematical models of real systems can help in the design and analysis of those systems. Finally, we have the more typical goals of teaching exciting and important basic material from electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making. (from ocw.mit.edu)
| Lecture 09 - Circuit Abstractions |
In this session, we use what we've learned in the previous two sessions to allow even further circuit abstraction. We'll learn about Thevenin equivalence (as well as Norton equivalence) and superposition.
| References |
| Circuit Abstractions | Unit 3 Readings. Lecture handout (PDF). Lecture slides (PDF). Recitation Videos. Session Activities. |
Go to the Course Home or watch other lectures:
| Unit 1: Software Engineering |
| Lecture 01 - Object-oriented Programming |
| Lecture 02 - Primitives, Combination, Abstraction, and Patterns |
| Unit 2: Signals and Systems |
| Lecture 03 - Signals and Systems |
| Lecture 04 |
| Lecture 05 - Characterizing System Performance |
| Lecture 06 - Designing Control Systems |
| Unit 3: Circuits |
| Lecture 07 - Circuits |
| Lecture 08 - Op-Amps |
| Lecture 09 - Circuit Abstractions |
| Unit 4: Probability and Planning |
| Lecture 10 - Discrete Probability and State Estimation |
| Lecture 11 |
| Lecture 12 - Search Algorithms |
| Lecture 13 - Optimizing a Search |