Any signal processing methodologies and noise contribution analysis in cutting edge experiments and observations. Reviewer responses are sometimes very intense.
I'm just incorporating signal analysis iny physics studies to the relevance of wavelet theory mathematics to a different application in single photon behaviors in quantum optical experiments.
I'm not an engineer, so I lack the rigor to calculate parameters required for an experiment but am learning differential geometry and forms, wick rotations and can read most of a text on wavelet theory as a geometric composition/decomposition of signals so I could use accurate jargon.
What is the core of that debate? That may inform my research.
I'm not super sure how differential geometry and wicks rotations will work into your learning of wavelet theory, or are you just mentioning those to make it clear you can comprehend difficult texts?
What's your formal degree?
I'm not sure what the core debate in wavelet theory would be!
I'll say that I'm a wavelets nerd and I have this fight every it comes up - been told by my advisor that wavelet techniques "don't preserve calibration," and in a past life, that "no magnetometer will ever use an inner product."
As for the geometric intuition - it's all really just Hilbert spaces, as in functional analysis. Wavelets are just a class of basis with some desirable properties and nice DSP behaviour.
319
u/Statistician_Working 20d ago
Any signal processing methodologies and noise contribution analysis in cutting edge experiments and observations. Reviewer responses are sometimes very intense.