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signals

Signals

Signals

Intro

"Simple" but Elegant Filters

Machine Learning for Signal Processing

    • Fun examples. Including figuring out nonlinear mappings of data (even into a jelly roll). Looks really difficult…
    • His mapping of distances to US cities (how did he do that??) is really similar to Gerritsen's “apply weighting by charge repelling and spring attracting” in her video.
    • He really likes Non-Negative Matrix Factorization…and it seems for good reason! smaragdis-waspaa2013keynote.pdf (view in Adobe Reader to get flash player). Another paper that uses it: smaragdis-spm2014.pdf
    • Excellent example of Expectation Maximization using looking at dice rolls. Makes much more intuitive sense than book explanations.

Pattern Recognition

Time Series Analysis

  • Also known as real-time trading, identification, etc
  • Great overview set of slides: http://alumni.cs.ucr.edu/~mvlachos/ICDM06/. Talks about dynamic time warping, lcss algorithm, pca, all vs correlation and talks about benefits and disadvantages.
    • Anything you do other than correlation will be more expensive to compute, but could “see” your signal a lot better in the midst of noise / time dilation, etc.
    • However, “The more complicated the algorithm, the less it works” –Bhiksha Raj ;-)

To Read

Books I Like

Understanding DSP (by Lyons)

Chapters 1-3
  • Periodic sampling of 250 Hz allows a 10 Hz signal to look like a -10 Hz signal and a 240 and 260 Hz signal in the frequency domain! Doesn't really matter in Matlab experimenting, but can screw you up when you are demodulating a signal or getting high frequencies corrupting your signal (because they too can be interpreted as a slow-moving sine wave).
  • Little difference between Hanning and Hamming windows, but you do want to use them! They reduce sidelobe leakage by a ton, but come at the cost of a 2X larger main lobe size.
FFT (Ch. 4)
  • Skipping for now…maybe I'll get more interested eventually. Basically, there are redundancies in computing the DFT (can halve spectrum computation w/ real input signals), and some other things I don't understand yet.

Books I Will Like

signals.txt · Last modified: 2017/09/15 17:58 (external edit)