3 ms·
1. The only thing that matters in engineering is the discrete Fourier transform (DFT). That’s what anyone who wants to calculate anything must use. 2. The fas
by aj7 7y ago
1. The only thing that matters in engineering is the discrete Fourier transform (DFT). That’s what anyone who wants to calculate anything must use.
2. The fast Fourier transform (FFT) is used to to calculate the DFT. Cue up Matlab or LabView.
3. Knowing the units of the abscissa in sample and frequency space is next.
4. Studying the sampling theorem so hard you can describe it in a number of different contexts, rigorously, is critical.
5. Knowing what aliasing and antialiasing are is critical.
6. Knowing how to use transforms to interpolate is next.
7. Knowing how to mess around with the real and imaginary parts of the complex DFT to improve the S/N is a good achievement.
8. Convolutional filters.
9. Smoothing data sets with non-causal filters.
10. What windowing functions, and why?
Have I left anything out?
- ta1234567890 7y agoWhere could someone go (ideally online) to learn those things and practice them?
- AareyBaba 7y agoI recommend Coursera Digital Signal Processing by Martin Vetterli https://www.coursera.org/learn/dsp https://www.coursera.org/learn/dsp. He does a good job of explaining the math behind the DFT. Any finite signal can be expressed as a linear combination of complex exponentials - that was the aha! moment for me. Once you have that under your belt you might find Audio Signal Processing for Music Applications by Xavier Serra a fun course to complete https://www.coursera.org/learn/audio-signal-processing https://www.coursera.org/learn/audio-signal-processing.
- bigger_cheese 7y ago"The Scientist and Engineer's Guide to Digital Signal Processing" by Steven W Smith available online here: http://www.dspguide.com/pdfbook.htm http://www.dspguide.com/pdfbook.htm One of my colleagues lent me a hardcover copy very good explanation I found it a huge help for a recent project I was working on (Sonic vibration sensor). Clearest explanation of everything I was able to find. Fourier transforms were covered during my engineering degree but it had been some years since I'd needed to concern myself with them. Top google hits were not really helping and I found this textbook was invaluable.
- aj7 7y agoI personally learned mostly from experiments in Labview. The Smith book is excellent.
- tanderson92 7y agoYes. The problem is assuming the only thing that matters with the fourier transform is the DFT. Point #1 is incorrect. Sometimes sampling theorems are misleading (not incorrect). There are cases where it is highly advantageous compute a continuous fourier transform without a DFT.
- aj7 7y agoI think my answer was highly oriented towards handling real data. But even in simulation, any calculations are discrete. It helps tremendously to understand continuous Fourier transforms, because most of the theorems have immediate discrete analogs.