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 
fxlms = dsp.FilteredXLMSFilter
returns
a filteredx Least Mean Square FIR adaptive filter System object, fxlms
.
This System object is used to compute the filtered output and
the filter error for a given input and desired signal.
fxlms = dsp.FilteredXLMSFilter('
returns
a PropertyName
', PropertyValue
,...)FilteredXLMSFilter
System object, fxlms
,
with each specified property set to the specified value.
fxlms= dsp.FilteredXLMSFilter(LEN,'
returns
a PropertyName
',PropertyValue
,...)FilteredXLMSFilter
System object, fxlms
,
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. 
msesim  Meansquare error for FilteredX LMS filter 
reset  Reset filter states for FilteredX LMS filter 
step  Apply FilteredX LMS filter to input 
Common to All System Objects  

clone  Create System object with same property values 
getNumInputs  Expected number of inputs to a System object 
getNumOutputs  Expected number of outputs of a System object 
isLocked  Check locked states of a System object (logical) 
release  Allow System object property value changes 
[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