Applied DSP No. 1: What is a signal?
Introduction to Applied Digital Signal Processing
What is a Signal?
- A signal can be defined as anything that provides information or data, with examples including electrocardiograms (ECGs), stock prices, sound, and light variations.
- The preferred definition of a signal is anything we can measure. This measurement occurs at regular intervals or sampling rates, which vary based on the nature of the phenomena being observed.
Measurement Intervals
- Different signals require different measurement frequencies; for instance, average global temperature might be measured annually while body temperature could be checked hourly.
- Some signals change rapidly, such as air pressure variations perceived as sound (thousands of times per second), or digital signals in computing (millions to billions of times per second).
Applications of Signal Processing
- Signal processing methods have broad applications across various fields including healthcare, financial modeling, media and entertainment, and modern communications.
- Proper signal processing is essential for AI systems that interpret signals to derive meaning—this process is referred to as going from "signal to symbol."
Course Overview
- The course will focus on hands-on projects related to digital signal processing (DSP), particularly through sound and music. No prior musical experience is required.
- Key topics include audio compression systems (like MP3), frequency spectrum analysis, sampling and quantization, time-frequency analysis, and digital filter design.
Course Structure