me 360: signal processing

Course Description:

ME 360 is a basic signals and systems class. Signals topics includes Fourier (frequency-domain) analysis for analog and discrete-time signals, transformations between time-domain and frequency domain representations, sampling and aliasing. Systems topics include Laplace and z-transforms and their relationship to impulse response and convolution. Basic applications of these concepts to signal processing (filter design), feedback control (PI control), and machine learning (perceptron and linear regression) will also be covered.


The current plan is that this course will be taught in person.The situation around Covid-related restrictions on campus can of course change at any moment, and I will keep the class updated of any developments.

Schedule: Mon Wed Fri 3:00 - 3:50 pm, 2233 Everitt Lab

Prerequisites: ME 340: Modeling and Analysis of Dynamic Systems (or equivalent)

Office hours: TBA

Homework TA: TBA

TA Office hours: TBA


  • Course Notes. Ambardar, Analog and Digital Signal Processing, 2nd Ed., 1999

Assignments and grading policy:

Your grades will be based on homework and exams. Details will be explained in class.

Lecture Notes:

  • Add notes/lecture links from here and so on