Geoscience Reference
In-Depth Information
b
a
d
c
Fig. 6.7
Output of the adaptive i lter.
a
h e duplicate records corrupted by uncorrelated
noise are fed into the adaptive i lter with 5 weights with a convergence factor of 0.0019. At er
20 iterations, the i lter yields
b
the learning curve,
c
the noise-free record, and
d
the noise
extracted from the duplicate records.
and
yn1'
), and
eig
returns the eigenvector of
k
. h is yields
u =
0.0019
We now run the adaptive i lter
canc
for 20 iterations and use the above value
of
u
.
[z,e,mer,w] = canc(yn1,yn2,0.0019,5,20);
h e output variables from
canc
are the i ltered primary signal
z
, the extracted
noise
e
, the mean-squared error
mer
for the number of iterations
it
performed
with stepsize
u
, and the i lter weights
w
for each data point in
yn1
and
yn2
. h e
