[V,D]=framemuleigs(Fa,Fs,s,K); D=framemuleigs(Fa,Fs,s,K,...);
Fa | Analysis frame |
Fs | Synthesis frame |
s | Symbol of Gabor multiplier |
K | Number of eigenvectors to compute. |
V | Matrix containing eigenvectors. |
D | Eigenvalues. |
[V,D]=framemuleigs(Fa,Fs,s,K) computes the K largest eigenvalues and eigen-vectors of the frame multiplier with symbol s, analysis frame Fa and synthesis frame Fs. The eigenvectors are stored as column vectors in the matrix V and the corresponding eigenvalues in the vector D.
If K is empty, then all eigenvalues/pairs will be returned.
D=framemuleigs(...) computes only the eigenvalues.
framemuleigs takes the following parameters at the end of the line of input arguments:
'tol',t | Stop if relative residual error is less than the specified tolerance. Default is 1e-9 |
'maxit',n | Do at most n iterations. |
'iter' | Call eigs to use an iterative algorithm. |
'full' | Call eig to solve the full problem. |
'auto' | Use the full method for small problems and the iterative method for larger problems. This is the default. |
'crossover',c | Set the problem size for which the 'auto' method switches. Default is 200. |
'print' | Display the progress. |
'quiet' | Don't print anything, this is the default. |
The following example calculates and plots the first eigenvector of the Gabor multiplier given by the batmask function. Note that the mask must be converted to a column vector to work with in this framework:
mask=batmask; [Fa,Fs]=framepair('dgt','gauss','dual',10,40); [V,D]=framemuleigs(Fa,Fs,mask(:)); sgram(V(:,1),'dynrange',90);