Signals and Systems

The Basics of Signals and Systems: A Detailed, Step-by-Step Guide

Introduction

A very important topic for any electronic engineer! This popular class provides students with a detailed, step-by-step guide to building signals and systems. In this class, you will learn how signals and systems are defined and used in electronics, how they are created and configured, and the essential structures involved in controlling and managing them. Besides electronics, you will learn about biological signal systems, chemical, thermal, and power systems. To illustrate, you will perform a variety of experiments using these systems. While building signals and systems, you will build up your knowledge of electrical concepts, circuit theory, and principles of mathematical logic, such as linear and nonlinear permutations and combinations.

What is a signal and system?

When I started learning signal and system theory, I was a bit skeptical of the utility of a textbook that claimed it was based on the assumptions of linear physics and chemistry, but that was all it was, was a claim. Upon learning that, my skepticism dissipated. To be honest, I was a bit skeptical of the utility of a textbook that claimed it was based on the assumptions of linear physics and chemistry, but that was all it was, was a claim. Linear physics and chemistry were not something that I knew. They were certainly not things that I had to know, in the real world, in order to understand how things worked. Signals and Systems was a quick and easy read and one that served as a good introduction to the subject matter.

Time-Domain Representation of a Signal

A time-domain representation of a signal, especially an amplitude signal, requires storing time information. The following are some common forms of time-domain representation for amplitude or frequency signals, all of which are not the only options.

Frequency-Domain Representations of Signals

In the frequency domain, a signal is represented as frequency with its usual units of hertz. The frequency represents the variation of the variable, and is what we hear. The width of the frequency domain is represented by Hertz. Frequency ranges from 0 to 15000 Hertz. So for instance, in the spectral domain, a signal can be described as frequency of electromagnetic waves, or gamma. For instance, a gamma wave represents the variation of electromagnetic waves in frequency. The frequency of gamma signals ranges from 0 to 30000. The spectral range is the same as that of the frequency domain: 0 to 15000 Hertz. This is the basic way that we understand the frequency domain. Then we have the frequency domain, where we often use the symbol for frequency, such as Ω (octave) or MHz (megahertz).

The Fourier Transform

Fourier transform is one of the most valuable tools that computers and scientists have. In particular, it has a fascinating capability for computing correlations. Specifically, Fourier transforms can be used to extract information about relationships between frequency, signal strength, and the path of signal propagation. The mathematical analysis can lead to entirely new ways of observing data. As it turns out, our senses are incredibly good at this! In this article, I’m going to discuss how to use the Fourier transform to understand the world around us. I’ll show you how to see in two dimensions using surface phenomena, and how to visualize a three-dimensional environment. I’ll also discuss some of the ways that mathematics applies to the world of signals and systems.

Conclusion

This short intro to signal and system analysis covers the basics, from the importance of knowing the difference between a signal and a system to the construction and application of both. As you progress, you’ll begin to learn more about different kinds of signal processing techniques (imaging, image and image processing, etc.) and how they apply to image capture and analysis.