This lesson introduces you to the concepts of “signals” and “signal processing” with computers. You will develop an appreciation for the incredible breadth of signal processing applications. You will also gain valuable perspective of key historical factors that have shaped the field. This information lays the foundation for you to be able to apply signal-processing […]
Foundations
Ever-Present Noise
The most dominant factors in the field of signal processing are noise and its sister, interference. Noise and interference is the motivating root of almost all signal-processing methods. This lesson introduces you to the notions of noise and interference and explains why they are always present. You will gain an understanding for the context for […]
Models, Math, and Real-World Signals
In this third lesson on fundamental signal processing concepts you will learn about the role of mathematical models in signal processing. Models are used to describe characteristics of signals and or noise that are relevant to the information of interest in the signal. Mathematical models underlie all algorithms in signal processing, including separation of signals […]
Four Signal-Processing Themes
This lesson introduces you to four common signal-processing problems that transcend many application areas. You will gain a general perspective of the overarching goals of the signal processing without the complications of specific applications and methods. This high level introduction will help you maintain the proper perspective and context when you later immerse yourself in […]
Jupyter Notebook: Explore FIR Filtering
Filters are used to change the character of signals in a desired manner. This activity will give you hands-on experience with simple filters and begin developing your intuition. You will see the effect of the filter in the graph and hear the effect via audio. The design of filters for specific purposes is an extensive […]
Jupyter Notebook: Explore Image Filtering
In this activity you will learn how simple image filters are used to modify the character of an image. A simple image filter replaces the value of each pixel with a weighted sum of the values of the neighboring pixels. The weights determine the nature of the filtering and can be chosen to accentuate edges […]
