Builds updated today with these changes:
- Added: Airy and Morlet continuous wavelet transform modes for the spectrogram graph
- Added: Export buttons for the decay, waterfall and spectrogram graphs
- Added: Export IR as WAV option to export a specified number of samples
- Added: IR windows dialog display of number of samples the windows span
- Added: Mouse wheel can be used to adjust sliders for the alignment tool and t=0 offset
- Added: Recommend the 64-bit build on 64-bit architectures
- Fixed: Generator might not start when attempting SPL calibration
The Airy CWT and Morlet CWT modes are Java implementations of a continuous wavelet transform using the algorithm described in Arts, L., & van den Broek, E. (2022). The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time–frequency analysis. Nat Comput Sci, 2(1), 47–58. https://doi.org/10.1038/s43588-021-00183-z
The Morlet wavelet is commonly used for CWT, though it has some deficiencies at high time resolutions, producing artefacts which are a consequence of it being only approximately analytic. The Airy wavelet is from the γ = 3 family of the generalised Morse wavelets. It is exactly analytic and has better performance than the Morlet wavelet at octave fractions from 1/1 to 1/5. At high frequency resolutions, octave fractions from 1/12 to 1/24, the Airy wavelet produces artefacts and the Morlet wavelet is a better choice.
REW's Wavelet mode implements the transform using complex smoothing and the time shift properties of the FFT, with a kernel that is less gaussian (tending more towards triangular) than Morlet or Airy. That gives sharper definition to higher level features of the plot at the expense of more low level artefacts.