[Lo_D,Hi_D,Lo_R,Hi_R] = wfilters(
[F1,F2] = wfilters(
[Lo_D,Hi_D,Lo_R,Hi_R] = wfilters( computes
four filters associated with the orthogonal or biorthogonal wavelet
named in the character vector
The four output filters are
Lo_D, the decomposition low-pass
Hi_D, the decomposition high-pass
Lo_R, the reconstruction low-pass
Hi_R, the reconstruction high-pass
Available orthogonal or biorthogonal wavelet names
listed in the table below.
[F1,F2] = wfilters( returns
the following filters:
% Set wavelet name. wname = 'db5'; % Compute the four filters associated with wavelet name given % by the input character vector wname. [Lo_D,Hi_D,Lo_R,Hi_R] = wfilters(wname); subplot(221); stem(Lo_D); title('Decomposition low-pass filter'); subplot(222); stem(Hi_D); title('Decomposition high-pass filter'); subplot(223); stem(Lo_R); title('Reconstruction low-pass filter'); subplot(224); stem(Hi_R); title('Reconstruction high-pass filter'); xlabel('The four filters for db5') % Editing some graphical properties, % the following figure is generated.
Daubechies, I. (1992), Ten lectures on wavelets, CBMS-NSF conference series in applied mathematics. SIAM Ed.
Mallat, S. (1989), "A theory for multiresolution signal decomposition: the wavelet representation," IEEE Pattern Anal. and Machine Intell., vol. 11, no. 7, pp. 674–693.