The dsp.FilteredXLMSFilter
computes output,
error and coefficients using FilteredX Least Mean Squares FIR adaptive
filter.
To implement the adaptive FIR filter object:
Define and set up your adaptive FIR filter object. See Construction.
Call step
to implement the filter
according to the properties of dsp.FilteredXLMSFilter
.
The behavior of step
is specific to each object in
the toolbox.
Note:
Starting in R2016b, instead of using the 
H = dsp.FilteredXLMSFilter
returns
a filteredx Least Mean Square FIR adaptive filter System object,
H. This System object is used to compute the filtered output and
the filter error for a given input and desired signal.
H = dsp.FilteredXLMSFilter('
returns
a PropertyName
', PropertyValue
,...)FilteredXLMSFilter
System object, H, with each
specified property set to the specified value.
H = dsp.FilteredXLMSFilter(LEN,'
returns
a PropertyName
',PropertyValue
,...)FilteredXLMSFilter
System object, H, with the
Length property set to LEN
, and other specified
properties set to the specified values. For the algorithm on how to
implement this filter, refer to [1], [2].

Length of filter coefficients vector Specify the length of the FIR filter coefficients vector as a positive integer value. This property is nontunable. The default value is 10. 

Adaptation step size Specify the adaptation step size factor as a positive numeric
scalar. The default value is 

Adaptation leakage factor Specify the leakage factor used in a leaky adaptive filter as
a numeric value between 

Coefficients of the secondary path filter model Specify the coefficients of the secondary path filter model as a numeric vector. The secondary path connects the output actuator and the error sensor. The default value is a vector that represents the coefficients of a 10thorder FIR lowpass filter. This property is tunable. 

An estimate of the secondary path filter model Specify the estimate of the secondary path filter model as a
numeric vector. The secondary path connects the output actuator and
the error sensor. The default value equals to the 

Initial coefficients of the filter Specify the initial values of the FIR adaptive filter coefficients
as a scalar or a vector of length equal to the value of the This property is tunable. 

Locked status of the coefficient updates Specify whether to lock the filter coefficient values. By default,
the value of this property is This property is tunable. 
clone  Create FilteredX LMS filter object with same property values 
isLocked  Locked status for input attributes and nontunable properties 
msesim  Meansquare error for FilteredX LMS filter 
release  Allow property value and input characteristics changes 
reset  Reset filter states for FilteredX LMS filter 
step  Apply FilteredX LMS filter to input 
[1] Kuo, S.M. and Morgan, D.R. Active Noise Control Systems: Algorithms and DSP Implementations. New York: John Wiley & Sons, 1996.
[2] Widrow, B. and Stearns, S.D. Adaptive Signal Processing. Upper Saddle River, N.J: Prentice Hall, 1985.
dsp.AdaptiveLatticeFilter
 dsp.AffineProjectionFilter
 dsp.FIRFilter
 dsp.FrequencyDomainAdaptiveFilter
 dsp.LMSFilter
 dsp.RLSFilter