You have probably heard the expression “it’s a digital world.” The problem is the world is really filled with heat, light, sound, voltage, movement and thousands of other naturally occurring signals which are all analog. As shown in this simplified picture analog signals are continuous streams of information. Digital signals are streams of signals either on or off, 1 or 0, which is why it is also known as binary code.

Analog v Digital

In the very early days of the development of the computer one of the biggest arguments was whether to work in analog (since the world is already analog) or in digital. Analog computers, while still in use today in certain applications, do not have the speed and accuracy of digital computers. With the advent of semiconductors digital computers became faster, smaller and used much less power and generated way less heat than their tube ancestors.

Okay, so today we have very fast digital computers, but we still have a world full of analog signals we need to measure and analyze. This is where data converters enter the picture. Turns out there are different ways of accomplishing the goal converting an analog signal into a digital stream. Some methods are better if you need to capture data faster (a good example would be cellular phone systems) others are for when you need to be extremely precise (such as in robot-assisted surgery); both present challenges not easily overcome. However, one of the most vexing challenges is known as aliasing.

To best explain aliasing I will take you back to one of my favorite interactive exhibits at a local science museum which, using a method pioneered by MIT’s Harold Edgerton, shone a stroboscopic light on a slow cascading stream of water. The coolest part was being able to control the speed of the strobe light. If you adjusted the speed just right it looked as if the drops of water were hanging in mid-air, not moving at all. Yet the water had never stopped moving, it was falling at the same rate. That is aliasing.

Edgerton Piddler

Edgerton’s “Piddler” waterfall strobe display (Courtesy DavidHazy.org)

 There’s a whole lot of math behind this simple example but don’t worry, we’re not going to go through it. The important thing to know about aliasing is how it can cause a converter to be unable to distinguish between two analog signals moving at different speeds. When that happens faulty data results and the systems relying on that data (could be healthcare devices or manufacturing equipment) are adversely affected. The best way to eliminate aliasing is to add special filters to the measuring circuit. Turns out filters of the required strength are not easy to build. They also tend to take up a lot of room on the circuit boards and can use a lot of power. Ironically, these filters can also introduce noise into the system (which kind of defeats the purpose of having them in the first place).

To solve the aliasing challenge ADI has developed the AD7134, a high-resolution (24 bit) analog-to-digital converter with  an incredibly stable, almost completely noise-free built-in filter which makes this converter alias free! Not only does this ensure the accuracy of our customers’ final product, but it saves them the time it would take to design and test their own filters. The built-in filter on the AD7134 also reduces the size of the solution by 70%.

side by side comparison with solution

A comparison of a high-resolution ADC with traditional discrete filter vs. the space and time-saving AD7134

More information about the alias-free, high-resolution AD7134 ADC is available on its product page here. There you can also find links to the datasheet and how to order samples as well as an evaluation board.

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There are plenty of articles and papers for those daring enough to dive deeper into this very important data conversion topic. Here are just a few from ADI authors:

AN-282 Fundamentals of Sampled Data Systems

11 Myths About Analog Noise Analysis

Filtering 101 Whiteboard Series

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