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6.01, Fall Semester, 2007—Lecture 1 Notes 1MASSACHVSETTS INSTITVTE OF TECHNOLOGYDepartment of Electrical Engineering and Computer Science6.01—Introduction to EECS IFall Semester, 2007Lecture 1 NotesGoals for 6.01We have a number of goals for this course. Our primary goal is to enhance your ability to solvecomplex problems by strengthening your skill in the most pervasive strategy for dealing with com-plexity: using abstraction and modularity. We will examine the use of abstraction and modularityin a number of contexts associated with problems in electrical engineering (EE) and computer sci-ence (CS), as we hope to help you develop a more fundamental understanding of abstraction andmodularity. We also hope that you will see more than just the similarities in broad perspective,but will also develop skills in using several specific abstraction strategies that have persisted in im-portance. To accomplish our primary goal, we will study how to analyze and design systems thatinteract with, and attempt to control, an external environment. Such systems include everythingfrom low-level controllers like heat regulators or cardiac pacemakers, to medium-level systems likeautomated navigation or virtual surgery, to high-level systems that provide more natural human-computer interfaces.Our second goal is for you to learn that making mathematical models of real systems can help inthe design and analysis of those systems; and to give you practice with building those models. Inparticular, we hope you will develop insight in to the difficult step of deciding which aspects of thereal world are important to the problem being solved, and then how to model in ways that giveinsight into the problem.We also hope to engage you more actively in the educational process. Most of the work of thiscourse will not be like typical problems from the end of a chapter. You will work individually andin pairs to solve problems that are deeper and more open-ended. There will not be a unique rightanswer. Argument, explanation, and justification of approach will be more important than theanswer. We hope to expose you to the ubiquity of trade-offs in engineering design. It is rare thata single approach will be best in every dimension; some will excel in one way, others in a differentway. Deciding how to make such trade-offs is a crucial part of engineering.Another way in which we hope to engage you in the material is by having many of you return to thecourse as a lab assistant. Having a large number of lab assistants in the course means that you canbe given more interesting open-ended design problems, because there will be staff readily availableto make sure you do not get stuck. Even more important, the lab assistants will question you asyou go; to challenge your understanding and help you see and evaluate a variety of approaches.This Socratic method has proven to be of great intellectual value to both classroom students andlab assistants.Finally, of course, we have the more typical goals of teaching exciting and important basic materialfrom electrical engineering and computer science, including modern software engineering, linearsystems analysis, electronic circuits, and estimation and decision-making. This material all has aninternal elegance and beauty, as well as crucial role in building modern EE and CS systems.6.01, Fall Semester, 2007—Lecture 1 Notes 2Modularity, abstraction, and modelingWhether proving a theorem by building up from lemmas to basic theorems to more specializedresults, or designing a circuit by building up from components to modules to complex processors,or designing a software system by building up from generic procedures to classes to class libraries,humans deal with complexity by exploiting the power of abstraction and modularity. And this isbecause there is only so much complexity a single person can hold in their head at a time.Modularity is the idea of building components that can be re-used; and abstraction is the idea thatafter constructing a module (be it software or circuits or gears), most of the details of the moduleconstruction can be ignored and a simpler description used for module interaction (the modulecomputes the square root, or doubles the voltage, or changes the direction of motion).One can move up a level of abstraction and construct a new module by putting together severalpreviously-built modules, thinking only of their abstract descriptions, and not their implementa-tions. This process gives one the ability to construct systems with complexity far beyond whatwould be possible if it were necessary to understand each component in detail.Any module can be described in a large number of ways. We might describe the circuitry in adigital watch in terms of how it behaves as a clock and a stopwatch, or in terms of voltages andcurrents within the circuit, or in terms of the heat produced at different parts of the circuitry. Eachof these is a different model of the watch. Different models will be appropriate for different tasks:there is no single correct model.The primary theme of this course will be to learn about different methods for building modulesout of primitives, and of building different abstract models of them, so that we can analyze orpredict their behavior, and so we can recombine them into even more complex systems. The samefundamental principles will apply to software, to control systems, and to circuits.Example problemImagine that you needed to make a robot that would roll up close to a light bulb and stop afixed distance from it. The first question is, how can we get electrical signals to relate to thephysical phenomena of light readings and robot wheel rotations? There is a whole part of electricalengineering related to the design of physical devices that that connect to the physical world in sucha way that some electrical property of the device relates to a physical process in the world. Forexample, a light-sensitive resistor (photoresistor) is a sensor whose resistance changes dependingon light intensity; a motor is an effector whose rotor speed is related to the voltage across its twoterminals. In this course, we will not examine the detailed physics of sensors and effectors, but willconcentrate on ways of designing systems that use sensors and effectors to perform both simpleand more complicated tasks. To get a robot to stop in front of a light bulb, the problem will be tofind a way to connect the photoresistor to the motor, so that the robot will stop at


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MIT 6 01 - LECTURE NOTES

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