When I do a Frequency Domain Decomposition (FDD) I always get mode shapes with significant imaginary components.

Let's say I see a strong modal response. Still have strong complex nature.

When I do a simple PCA of the dataset I can "see" the same shape in the dominant mode, but obviously no imaginary component.

So I interpret the complex values from the FDD as basically being a better fit to the data, with a phase component being permitted.


  1. Is that interpretation accurate?
  2. Is there a good way to go from the FDD shape to a non-complex shape? Taking the real doesn't work, nor the magnitude (all positive)?

Should I just be using the FDD to identify frequencies of interest, bandpass filter before PCA?


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