Brief Introduction
Enter the world of signal processing: analyze and extract meaning from the signals around us!
Description
Coming Soon February 2021. Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data?
Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required).
Learners should have strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.
Coaching
If you are enrolled in the verified track (paid track) in any course that is a part of a MicroBachelors program, including this course, you are eligible for coaching at no additional cost. Please note that coaching is only available via SMS to U.S. phone lines.
Our coaches (real humans) are ready to help you with career exploration, navigating resources, staying motivated, and solving problems along the way to your goals.
Learn more about the value of coaching directly from one of our coaches, Erin.
Knowledge
- Types of Fundamental Signals
- Vector Description of Signals
- Introduction to Discrete Time Systems
- Convolution
- The Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT)
- The Discrete-Time Fourier Transform (DTFT)
- The Z-Transform
- Introduction to Analysis and Design of Discrete-Time Filters
Digital Signal Processing (DSP) From Ground Up™ in Python
- 4.3
-
![]()
![]()
![]()
![]()
![]()
Practical DSP in Python : Over 70 examples, FFT,Filter Design, IIR,FIR, Window Filters,Convolution,Linear Systems etc This version of the course uses the Python programming language....
The Finite Element Method for Problems in Physics
- 4.6
-
![]()
![]()
![]()
![]()
![]()
This course is an introduction to the finite element method as applicable to a range of problems in physics and engineering sciences....
Statistical Mechanics: Algorithms and Computations
- 4.8
-
![]()
![]()
![]()
![]()
![]()
Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach....
Machine Learning Data Lifecycle in Production
- 4.5
-
![]()
![]()
![]()
![]()
![]()
Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well....
