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[DOC] Explain STFT dimension discrepancy in accelerometer data processing #42

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opened 2025-04-19 15:39:53 +00:00 by nuluh · 0 comments
nuluh commented 2025-04-19 15:39:53 +00:00 (Migrated from github.com)
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Documentation Type

Methodology Description

Description

Need to document the explanation for the STFT dimension discrepancy in accelerometer data processing. Specifically, explain why 262,144 time-domain data points processed with STFT (window size=1024, hop size=512) results in magnitude shape (513,513) instead of the expected (513,511).

Current State

No response

Proposed Changes

  1. Add a paragraph in Section X.Y explaining the STFT dimension calculations
  2. Include mathematical explanation for expected dimensions (513,511)
  3. Explain how missing the 'boundary=zeros' parameter affects the output dimensions
  4. Provide a small figure/diagram illustrating the windowing effect if appropriate
  5. Add a note about how this affects subsequent processing steps

Documentation Location

latex/chapters/methodology/signal_processing.tex

Priority

Medium (helpful but not urgent)

Target Audience

Thesis Committee/Reviewers

References

  • Source code in src/preprocessing/stft_transform.py
  • https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.stft.html
    • Oppenheim, Alan V., Ronald W. Schafer, John R. Buck “Discrete-Time Signal Processing”, Prentice Hall, 1999.
    • Daniel W. Griffin, Jae S. Lim “Signal Estimation from Modified Short-Time Fourier Transform”, IEEE 1984, 10.1109/TASSP.1984.1164317
  • My experiment notebook: notebooks/signal_transformation_analysis.ipynb

Additional Notes

This explanation is critical for reproducibility of my results and demonstrates understanding of the signal processing fundamentals. Will include code snippet showing the parameter's effect.

### Documentation Type Methodology Description ### Description Need to document the explanation for the STFT dimension discrepancy in accelerometer data processing. Specifically, explain why 262,144 time-domain data points processed with STFT (window size=1024, hop size=512) results in magnitude shape (513,513) instead of the expected (513,511). ### Current State _No response_ ### Proposed Changes 1. Add a paragraph in Section X.Y explaining the STFT dimension calculations 2. Include mathematical explanation for expected dimensions (513,511) 3. Explain how missing the 'boundary=zeros' parameter affects the output dimensions 4. Provide a small figure/diagram illustrating the windowing effect if appropriate 5. Add a note about how this affects subsequent processing steps ### Documentation Location latex/chapters/methodology/signal_processing.tex ### Priority Medium (helpful but not urgent) ### Target Audience Thesis Committee/Reviewers ### References - Source code in src/preprocessing/stft_transform.py - https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.stft.html - Oppenheim, Alan V., Ronald W. Schafer, John R. Buck “Discrete-Time Signal Processing”, Prentice Hall, 1999. - Daniel W. Griffin, Jae S. Lim “Signal Estimation from Modified Short-Time Fourier Transform”, IEEE 1984, 10.1109/TASSP.1984.1164317 - My experiment notebook: notebooks/signal_transformation_analysis.ipynb ### Additional Notes This explanation is critical for reproducibility of my results and demonstrates understanding of the signal processing fundamentals. Will include code snippet showing the parameter's effect.
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Reference: nuluh/thesis#42
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