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Convolution - a visual Digital Signal Processing tutorial
Fourier theory says that any periodicsignal can be created by adding together different sinusoids (of varying frequency, amplitude and phase). In many applications, an unknown analog signal is sampled with an A/D converter and a Fast Fourier Transform (FFT) is performed on the sampled data to determine the underlying sinusoids. In this 7-step tutorial, a visual approach based onconvolution is used to explain basic Digital Signal Processing (DSP) up to the Discrete Fourier Transform (DFT). The DFT is explained instead of the more commonly used FFT because the DFT is much easier to understand. (The DFT is equivalent to the FFT except the DFT is far less computationally efficient.) In particular, convolution is shown to be the key to understanding basic DSP. Also, some of the concepts are far more intuitive in the frequency-domain vs. the more familiar time-domain. Note: The distinction between continuous and discrete systems is blurred in this tutorial since the concepts are similar for both. Most of the following figures show continuous signals (except where as noted) for clarity because sampled signals are literally discrete (i.e. “dots”) and have the added complication of spectral replicas as will be explained in Step 6.
dsp  pdf  convolution  tutorial  mathematics  modular  audio  synthesis  reverb 
4 days ago by patrickod
Music 320
Music 320 - Introduction to Audio Signal Processing
ccrma  intro  to  audio  dsp  syllabus 
14 days ago by gdw

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