Compute forward SGWT for signal f (without frame calculation). The calculation corresponds to the frame defined by the `tight_frame` function (without explicit calculation of the latter).
forward_sgwt(f, evalues, evectors, b = 2)
wc
wavelet coefficients.
Graph signal to analyze.
Eigenvalues of the Laplacian matrix.
Eigenvectors of the Laplacian matrix.
Parameter that control the number of scales.
Göbel, F., Blanchard, G., von Luxburg, U. (2018). Construction of tight frames on graphs and application to denoising. In Handbook of Big Data Analytics (pp. 503-522). Springer, Cham.
de Loynes, B., Navarro, F., Olivier, B. (2021). Data-driven thresholding in denoising with Spectral Graph Wavelet Transform. Journal of Computational and Applied Mathematics, Vol. 389.
Hammond, D. K., Vandergheynst, P., & Gribonval, R. (2011). Wavelets on graphs via spectral graph theory. Applied and Computational Harmonic Analysis, 30(2), 129-150.
inverse_sgwt
, tight_frame