![]() ![]() Let’s use the same signal as the previous tutorial as our example signal: In practice, it is helpful to zero pad a signal to 4 times it’s original length, giving you a 4-fold increase in the frequency resolution. ![]() In general, zero-padding can prove quite useful and should be used when using the fft command. ![]() We’ll discuss why quotes are used around better in a bit. Another reason for zero-padding is for a “better” resolution in the frequency spectrum. Nowadays, this isn’t as important with the modern algorithms. Traditionally, the FFT algorithm is more efficient when it is dealing with signals that contain 2^N data points. Two reasons that you might want to zero pad is to increase the number of data points to a power of 2. ![]() Luckily, the fft command within Matlab makes it very easy to zero-pad. Zero-padding means that you append an array of zeros to the end of your input signal before you fft it. In this post, we will be discussing zero-padding, a method that can help you better visualize/interpret your fft results. In the previous tutorial, we showed you how correctly scale your x-axis so that your FFT results were meaningful. This is the fourth post in the blinkdagger signal processing series. ![]()
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May 2023
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