Introduction to CoE 161

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Welcome to CoE 161 / CoE 197!

Since we are offering this class remotely, there will be many changes to our normal course delivery:

  1. There will be no face-to-face lecture classes. All the material will be made available via this site.
  2. There will be more emphasis on student-centric activities, e.g. analysis, design, and simulations. Thus, you will be mostly "learning by doing". In this context, we will set aside an hour every week for consultations and questions via video-conferencing.
  3. Grades will be based on the submitted deliverables from the activities. Though we will not be very strict regarding the deadlines, it is a good idea to keep up with the class schedule and avoid cramming later in the semester.
Please remember that this semester is very different from those before, and please make sure you inform me if you have any issues or difficulties regarding the class. Also, keep in mind that you will need to pay a bit more attention to your time management as it will play a critical role during the course of the semester.

Let's get started!

Measuring Complexity

For any system we are studying, designing, or building, an interesting and important question is usually: "How complex is this system?" or "How complex should this system be?".

In general, we want to be able to compare two systems, and be able to say that one system is more complex than the other. In this case, having a numerical metric would be very convenient.

Basics of Information Theory

Introducing Entropy

The Gibbs Inequality

A First Look at Shannon's Communication Theory

Shannon's Theory for Analog Channels

Kullback-Leibler Information Measure

References