A guided journey · 20 lessons
Signal processing
From waves and sampling to spectra, filters and a denoising investigation.
Prerequisites are included automatically. Suggested lesson time: 9 hours, plus extra time for experimentation and projects. This is an estimate, not a measured completion time.
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- What is a signal?What does a waveform actually tell you?
- Frequency, amplitude and phaseHow can three numbers describe an oscillation?
- Vectors and similarityHow does a list of numbers become a geometric object?
- Complex numbers and rotationWhy do transforms use an imaginary coordinate?
- Slopes and gradientsHow do you decide which way to change a parameter?
- Probability and uncertaintyHow should several plausible outcomes share one unit of probability?
- Noise and signal-to-noise ratioHow much unwanted variation is in a measurement?
- Sampling and timeHow do equally spaced measurements encode motion?
- Aliasing and NyquistCan different waves produce exactly the same samples?
- Quantisation and clippingWhat changes when sample values have a finite alphabet?
- Resampling safelyWhy is keeping every other sample sometimes wrong?
- Projection onto wavesHow can a dot product detect a frequency?
- The discrete Fourier transformWhat exactly is in an FFT output array?
- Windows and leakageWhy does one tone make many spectral bars?
- Time-frequency analysisWhat if the signal’s frequency changes over time?
- Linearity and time invarianceWhen can one impulse response describe a whole system?
- Convolution step by stepWhich input samples contribute to one output?
- Frequency response and filter trade-offsWhy does averaging suppress some frequencies more than others?
- Recurrence and stabilityWhen does yesterday’s state fade, persist or explode?
- Project: a denoising pipelineCan you reduce interference without hiding signal distortion?
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