Just an update for the last post, even though it's really old now:
This library, HarmInv, from MIT, would have done the frequency estimation job just right. Too bad I didn't know about it. It actually decomposes a signal into a finite sum of exponentially decaying sinusoids, without doing a least mean squares regression (which could lack robustness, since it's not a linear problem in this case). Brilliant idea!
Since this summer, I had some image processing classes, and I can think of a million other ways of doing this over, harder, better, faster, stronger. I'll probably come back to it later. Specifically, the Hough transform was a nice idea to play around with, but it's really overkill and some form of prediction (using a Kalman filter for example) would have been nice.
This library, HarmInv, from MIT, would have done the frequency estimation job just right. Too bad I didn't know about it. It actually decomposes a signal into a finite sum of exponentially decaying sinusoids, without doing a least mean squares regression (which could lack robustness, since it's not a linear problem in this case). Brilliant idea!
Since this summer, I had some image processing classes, and I can think of a million other ways of doing this over, harder, better, faster, stronger. I'll probably come back to it later. Specifically, the Hough transform was a nice idea to play around with, but it's really overkill and some form of prediction (using a Kalman filter for example) would have been nice.
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