1-D approximation coefficients
A = appcoef(C,L,'
A = appcoef(C,L,
A = appcoef(C,L,Lo_R,Hi_R)
A = appcoef(C,L,Lo_R,Hi_R,N)
appcoef is a one-dimensional
wavelet analysis function.
appcoef computes the
approximation coefficients of a one-dimensional signal.
A = appcoef(C,L,' computes
the approximation coefficients at level
the wavelet decomposition structure
wavedec for more information).
'wname' is a character vector containing
the wavelet name. Level
N must be an integer
A = appcoef(C,L, extracts
the approximation coefficients at the last level: length
Instead of giving the wavelet name, you can give the filters.
A = appcoef(C,L,Lo_R,Hi_R) or
the reconstruction low-pass filter and
the reconstruction high-pass filter (see
This example shows how to extract the level 3 approximation coefficients.
Load the signal consisting of electricity usage data.
load leleccum; sig = leleccum(1:3920);
Obtain the DWT down to level 5 with the
[C,L] = wavedec(sig,5,'sym4');
Extract the level-3 approximation coefficients. Plot the original signal and the approximation coefficients.
Lev = 3; a3 = appcoef(C,L,'sym4',Lev); subplot(2,1,1) plot(sig); title('Original Signal'); subplot(2,1,2) plot(a3); title('Level-3 Approximation Coefficients');
You can substitute any value from 1 to 5 for
Lev to obtain the approximation coefficients for the corresponding level.
The input vectors
all the information about the signal decomposition.
NMAX = length(L)-2; then
[A(NMAX) D(NMAX) ... D(1)] where
D are vectors.
N = NMAX, then a simple extraction is
iteratively the approximation coefficients using the inverse wavelet
Usage notes and limitations:
Variable-size data support must be enabled.