Analog vs. Digital Signals

Do you remember the days of cassette tapes, VCRs, and analog TVs? If so, then you probably remember fuzzy pictures and the sound of static (Figure 1). Newer technologies like CDs, DVDs, Blu-Ray, and digital TVs are seemingly devoid of these problems—but why? This occurs because of an important difference between analog and digital signals. This section will give an overview of what analog and digital signals are, and how they are different.

Figure 1. Static on an older analog TV (left), and a "no signal" message on a newer digital TV (right).

First, we will use an example you are familiar with from your everyday life, especially as a teacher: writing. You probably have some students who have sloppy handwriting and some with "perfect" handwriting. But even if you ask a student with "perfect" handwriting to write the same letter of the alphabet over and over again, no two letters will be exactly the same (Figure 2). Handwritten letters are analog, meaning they can vary continuously. The position of the pencil tip and how hard you press down on the paper will always change slightly when you write, even if it is by a very small amount. This can result in small changes in the position or thickness of the line. Conversely, try typing the same letter repeatedly on a computer. Each instance of the letter will look exactly the same. These letters are digital, meaning they cannot vary continuously—they can only take on a discrete (or finite) set of values. There are a finite number of pixels on your computer screen, and (assuming we are typing black text on a white background) each pixel will either be black or white. So, for a fixed font, each copy of the same letter will look exactly the same.

Figure 2. Handwriting, which is analog, (left) vs. typing on a computer, which is digital (right).

So, what do we mean by a "signal"? A signal can be any method to transmit information over a distance. Humans had plenty of ways to do this before modern electronics (e.g. smoke signals, lighthouses, signal fires, drums/horns, etc.). In modern times, when we talk about signals, we are usually referring to electronic signals that are either sent through wires, or wirelessly through the air as electromagnetic waves. If you have ever plugged a video game console into a TV with a video cable, or connected your phone/laptop to Wi-Fi, then you have witnessed those devices using electronic signals to send information.

Like with our handwriting example, an analog signal has a value that can vary continuously. What does that mean? It helps to visualize signals using a graph where the x-axis is time and the y-axis is the value of the signal, like Figure 3 (for our purposes here, we will not worry about the units of the y-axis, since they depend on the specific type of signal). The graph is "squiggly," and the y-value (in this example) can be anything between 0 and 1.

Figure 3. An example analog signal.

A digital signal can only take on certain, discrete values. In its simplest form, the signal can be binary, meaning it can only take on two values: high or low (also referred to as on/off, true/false, or one/zero). Again, we can visualize this using a graph, like Figure 4. This graph is a "square wave"—the y value is either 0 or 1, but nothing in between.

Figure 4. Example digital signal.

So, what is important about that difference? All electronic signals are subject to noise (meaning electronic noise, not necessarily the kind you can hear with your ears), which can affect the value of the signal. Noise can be introduced by other nearby electronic devices, by transmitting signals over very long distances, or by copying a signal over and over. Figures 5 and 6 show our example analog and digital signals with noise added.

Figure 5. Example analog signal with noise added.

Figure 6. Example digital signal with noise added.

Look at Figures 5 and 6—can you guess why digital signals are better for storing or transmitting information? Even with noise added, you can still clearly tell whether any point in the digital signal is "high" or "low" (e.g. a value of 0.93 or 1.1 on the y-axis still counts as "high," even though it is not exactly 1.0). However, adding noise makes it impossible to recover the exact original values in the analog signal. For example, in Figure 3, at time = 1 second, the y-value of the graph is exactly 0.5. But in Figure 5, with noise added, the y-value at time =  1 second is 0.54—the value has changed! There is no way to know that the original value was supposed to be exactly 0.5.

Now imagine that the analog signal is being sent through a cable from your VCR to your TV, and the y-value represents the brightness of a pixel on the screen. If that value is subject to noise (and this occurs for all the pixels, not just one of them), it will result in a fuzzy or distorted image. However, for the digital signal, all the 1's and 0's arrive intact (they never get "flipped" to the opposite value), so the data does not get distorted at all.

That might sound like a lot of information for your students to absorb, but do not worry. You will start the lesson off with something much more student-friendly: drawing and tracing. They will see how tracing something drawn freehand onto printer paper (analog, because the line can vary continuously) compares to tracing something drawn on graph paper by filling in squares (digital, because each square can only be one of two values—filled in or blank). Then, you will use a mobile phone and a sensor app to experiment with sending analog and digital signals in your classroom and see how they are affected by noise.