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GSP_DESIGN_HEAT - Design a simple heat kernel
Usage
gsp_design_heat(G); gsp_design_heat(G,tau); gsp_design_heat(G,tau,param);
Input parameters
| G | Graph structure |
| tau | scaling parameter (default 10) |
Output parameters
| g | filter |
Description
This function design the following filter:
\begin{equation*}
g(x) = e^{-\tau \frac{x}{\lambda_{\text{max}}}}
\end{equation*}
If tau is a vector, the function returns a cell array of filters.
param is an optional structure containing the following fields
- param.verbose: verbosity level. 0 no log - 1 display warnings. (default 1)
- param.normalize: Normalize the kernel (works only if the eigenvalues are present in the graph. Use gsp_compute_fourier_basis for this.) (default 0)
This function will compute the maximum eigenvalue of the laplacian. To be more efficient, you can precompute it using:
G = gsp_estimate_lmax(G);
Example:
Nf = 4; G = gsp_sensor(100); G = gsp_estimate_lmax(G); g = gsp_design_heat(G); gsp_plot_filter(G,g);
