xo=largestn(x,N); xo=largestn(x,N,mtype);
largestn(x,N) returns an array of the same size as x keeping the N largest coefficients.
largestn takes the following flags at the end of the line of input arguments:
| 'hard' | Perform hard thresholding. This is the default. |
| 'wiener' | Perform empirical Wiener shrinkage. This is in between soft and hard thresholding. |
| 'soft' | Perform soft thresholding. |
| 'full' | Returns the output as a full matrix. This is the default. |
| 'sparse' | Returns the output as a sparse matrix. |
If the coefficients represents a signal expanded in an orthonormal basis then this will be the best N-term approximation.
Note: If soft- or Wiener thresholding is selected, only \(N-1\) coefficients will actually be returned. This is caused by the N'th coefficient being set to zero.
S. Mallat. A wavelet tour of signal processing. Academic Press, San Diego, CA, 1998.