The dsp.AdaptiveLatticeFilter
computes output,
error, and coefficients using a Lattice based 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.AdaptiveLatticeFilter
.
The behavior of step
is specific to each object in
the toolbox.
Note:
Starting in R2016b, instead of using the 
alf = dsp.AdaptiveLatticeFilter
returns
a Lattice based FIR adaptive filter System object, alf
.
This System object is used to compute the filtered output and
the filter error for a given input and desired signal.
alf = dsp.AdaptiveLatticeFilter('
returns
an PropertyName
', PropertyValue
,...)AdaptiveLatticeFilter
System object, alf
,
with each specified property set to the specified value.
alf = dsp.AdaptiveLatticeFilter(LEN,'
returns
an PropertyName
',PropertyValue
,...)AdaptiveLatticeFilter
System object, alf
,
with the Length property set to LEN
and other specified
properties set to the specified values.

Method to calculate filter coefficients Specify the method used to calculate filter coefficients as
one of 

Length of the 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 32. 

Leastsquares lattice forgetting factor Specify the Leastsquares lattice forgetting factor as a scalar
positive numeric value less than or equal to 1. Setting this value
to 1 denotes infinite memory during adaptation. This property applies
only if the Method property is set to This property is tunable. 

Joint process step size of the gradient adaptive filter Specify the joint process step size of the gradient adaptive
lattice filter as a positive numeric scalar less than or equal to
1. This property applies only if the This property is tunable. 

Offset for denominator of StepSize normalization term Specify an offset value for the denominator of the This property is tunable. 

Reflection process step size Specify the reflection process step size of the gradient adaptive
lattice filter as a scalar numeric value between 0 and 1, both inclusive.
Use this property only if the This property is tunable. 

Averaging factor of the energy estimator Specify the averaging factor as a positive numeric scalar less
than 1. Use this property to compute the exponentially windowed forward
and backward prediction error powers for the coefficient updates.
This property applies only if the This property is tunable. 

Initial prediction error power Specify the initial values for the prediction error vectors as a scalar positive numeric value. If the This property is tunable. 

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 applicable only if the This property is tunable. 
msesim  Meansquare error for Adaptive Lattice filter 
reset  Reset filter states for Adaptive Lattice filter 
step  Apply Adaptive Lattice 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] Griffiths, Lloyd J. "A Continuously Adaptive Filter Implemented as a Lattice Structure". Proceedings of IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Hartford, CT, pp. 683–686, 1977 .
[2] Haykin, S. Adaptive Filter Theory, 4th Ed. Upper Saddle River, NJ: Prentice Hall, 1996.
dsp.AffineProjectionFilter
 dsp.FilteredXLMSFilter
 dsp.FIRFilter
 dsp.FrequencyDomainAdaptiveFilter
 dsp.LMSFilter
 dsp.RLSFilter