Or at least “explain it like I am an 8th grader.” I am a middle school science teacher and am struggling with explaining these concepts in a simplified way that my students can understand. They have some prior knowledge about waves and how they travel. I appreciate any help you can provide!
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Analog signals are more like a dimmer switch for the light, where you can make it as bright or as dim as you want. It’s like having a light that can be a little bit bright, somewhat bright, very bright, or anywhere in between.
Digital has just two options (on or off), while analog can have lots of options (from a little bit to a lot).
Think of it like light switches.
A digital signal is either off or on. There’s voltage on the line or there isn’t.
An analog signal is like a dimmer switch. You can put any voltage on the line and it will have a discrete effect.
Analog means information is translated between different physical properties. Like sound waves into grooves on a record, or magnetic tape, or electrical signals, or radio waves, and then back into sound waves. Or light captured on sensitive film, then developed and printed or projected.
Digital (as in the digits in a number) means physical information is translated into binary data, stored or transferred by computers, then decoded back into physical information.
Sound waves are analog; Music! Digital signals are like Morris Code; Dots and Dashes(zeros and ones)[Software translates digital signals into analog so we can listen to… Taylor Swift].
This won’t be much help to you, but The basic confusion comes from the fact that there is no natural distinction between the two.
An analog signal is a physical phenomenon on a continuum, like voltage, which has been assigned meaning by a human. E.g. The correspondence between fuel.level in a gastank, And The voltage produced by the level sensor in the tank.
It is “Digital” when a human divides the continuous range of possibilities into three (or more) parts. E.g. In a 5 volt system, voltages between 0 and 1 volt are called “low” and between 4 and 5 volts are called “high”. Voltages between 1 and 4 volts have no meaning.
Low and High are often interpreted as the binary numbers 0 and 1, because that interpretation allows for some very nifty circuits to be built that can do arithmetic and (with more human interpretation) symbolic calculations.
But don’t lose sight of the fact that, fundamentally, it’s all analog, just with elaborate, human-designed, interpretations.
The word analog comes from the same root as analogy. Analog signals are generally continuous, and on a spectrum, like the information that describes waves. For sound wave information, an analog encoding might be the groove on a vinyl record.
Digital signals deal with digits. We encode data into discrete quantities which we can represent as numbers. This is why digital signals have an inherent “resolution”. For sound wave information, this resolution is the bitrate and the encoding would be a long string of binary information.
Another example would be clocks.
An analog clock has gears turning the hour, minute and second hands as time passes (the time units are an *analogy* for the physical processes taking place)
A digital clock counts up electronically. There’s no in-between states when voltages are either high or low. 1 or 0. It’s not continuous like time itself.
Turn on the water faucet and just let the water run. That’s an analog signal, because the water is continuously coming out, with no breaks.
Turn the water faucet on and off repeatedly. That’s a digital signal, because the water is coming out in discreet chunks, with breaks between each chunk.
Telephone vs. telegraph. They both use the same infrastructure, but in very different ways.
Telephone is analog: The sound wave is captured and turned into an electrical signal shaped exactly like the sound wave, which is sent down the wire and converted back. An old phone connected to a landline is nothing more than a microphone and a speaker, which connects to a corresponding speaker and microphone on the other end.
Telegraph is digital: You send on/off pulses and come up with an encoding scheme, such as Morse code. It’s exactly like having a light switch on one end, and a light bulb on the other, and flicking the light on and off to send a message.
The fact that you can represent an analog signal via a digital signal (the sampling theorem) is sort of separate and tends to confuse things. The key thing is that analog uses the exact voltage to convey information, digital uses high/low (on/off) in discrete pulses.
The distinction is more important in why we use them than what they are.
Analog signals are taking and manipulating information as is. A 2 khz wave at a certain voltage and power will produce a tone at a known volume. Increase the voltage and increase the volume. This makes things easy, but it comes with a problem: your signal is never pure. It will pick up environmental noise, and at every step you will be processing the noise with it. This is not much of an issue when you have a lot of power behind your signal, such as with powering a speaker.
Now let’s say you want to send that signal 2 miles to a cell tower using a couple milliwatts of power. The environmental noise is now almost as strong as the signal itself. Digital signals are our solution to this. The high/low nature of a digital signal allows us to eliminate noise. The first set of processing will clean the signal up and essential it will stay clean without additional filtering.
So while in a textbook an analog signal will look like sine waves and digital will look like square waves, in the real world what gets sent wirelessly often looks like an indiscernable mess, so digital signals are used because it is easier to reconstruct it without losing infornation.
The term “digital” is in some ways confusing. Yes, digital signals depend on numbers to work, but I’m going to call them “descriptive signals”. You’ll see why in a bit.
When you send an analog signal, you build a model of the thing you want to send. Usually the form differs, but you can still see the original if you know how to look at it. A landline phone is the classic example. You speak. A microphone picks up the sound waves and converts them to a fluctuating voltage. But if you plot out that voltage over time on a graph, it looks like the sound wave did. This signal goes to a speaker on the other end, which can convert that fluctuating voltage into sound waves, and since the voltage looks like the sound waves for wbat you said, the speaker outputs something that sounds like what you said. Let’s say that instead of going to a speaker, you fed the signal to a vibrating vinyl cutter, for making a record. It traces a groove into the disc, but if you look at those grooves in a microscope, they *also* look like the sound wave. This is the key to understanding analog signals: at every step, you’re creating a model of the previous step, just in a different form.
Digital signals -or rather, descriptive signals- work in a fundamentally different manner. Rather than making an entire model of the thing you want to transmit, you describe it in some agreed-upon manner. When you make a digital recording, a computer analyzes the sounds you make and builds up a description of the waveform. A player then takes this description and builds a waveform that fits that description. How good the new sound is depends on how well the original computer was able to describe it.
Which is better? In some ways, that depends on what you want to do. Descriptive signals are typically easier and less error-prone to copy. Anything that interferes with an analog signal becomes part of the signal, and can be very difficult to remove. With descriptive signals, only the things you’ve defined to be part of the description actually matter, so interference is usually easier to spot, and then you can ignore it or correct it. Descriptive signals are rarely perfect -descriptions can only go into so much detail- but because of the interference problem, analog signals aren’t usually perfect either. The interference problem becomes a big issue for copying analog signals, because imperfections in the machinery add up over time, while those imperfections generally don’t matter for descriptive signals anyway.
But my favorite example, sadly, may be out of reach now. See if your school’s library still has any microfiche equipment (it probably doesn’t, but check). This was popular for storing periodicals like newspapers and magazines before the advent of mass storage like CD-ROM. Newspapers are not yet so obscure that your students wouldn’t have seen them, and you can imagine how much room it would take to store an entire year’s worth of them. How did libraries handle these huge numbers of periodicals, back before the invention of digital storage? The analog solution was to literally make the periodicals smaller: they took photographs on these plastic sheets and shrunk them down very small. Microfiche readers are essentially small projectelors that enlarge the image so humans can read them, but you also read them with a microscipe if you really had to. This is the analog form of compression: to shrink the signal, make a model that’s actually smaller (in whatever way you need it to be smaller).
Digital -or rather, descriptive compression- works differently. You have to somehow make the description more concise. You can decide that some things don’t matter and just throw those pieces away: this is *lossy encoding*, because anything you throw away is just lost. As long as you’re judicious about what you throw away, this can be very efficient, but you have to be careful not to throw anything that’s actually important, or people will notice. Or, you can try to find a more efficient way to say your description, without actually throwing anything out. For example, if some long string gets repeated a few times, you might replace them with a short code that means the longer string. You also have to store a dictionary for these codes, but if the longer strings are repeated many times, you can still save space overall. This is *lossless compression*.
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