User`s guide

LMS Adaptive Filter
5-269
scalars. The signal at the Out port is a scalar, while the signal at the Taps port
is a sample-based vector.
An optional
Adapt input port is added when the Adapt input check box is
selected in the dialog box. When this port is enabled, the block continuously
adapts the filter coefficients while the
Adapt input is nonzero. A zero-valued
input to the
Adapt port causes the block to stop adapting, and to hold the filter
coefficients at their current values until the next nonzero
Adapt input.
The
FIR filter length parameter specifies the length of the filter that the LMS
algorithm estimates. The
Step size parameter corresponds to µ in the
equations. Typically, for convergence in the mean square, 0<µ<2. The
Initial
value of filter taps
specifies the initial value as a vector, or as a scalar
to be repeated for all vector elements. The
Leakage factor specifies the value
of the leakage factor, , in the leaky LMS algorithm below. This
parameter must be between 0 and 1.
Examples The lmsdemo demo illustrates a noise cancellation system built around the
LMS Adaptive Filter block.
Block Ports Corresponding Variables
In
u, the scalar input, which is internally buffered into the
vector u(n)
Out
y(n), the filtered scalar output
Err
e(n), the scalar estimation error
Taps
, the vector of filter-tap estimates w
ˆ
n()
w
ˆ
0()
1 µα–
w
ˆ
n 1+()1 µα–()ω
ˆ
n()
un()
u
H
n()un()
-----------------------------
µe
∗
n()+=