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Owning Palette: Adaptive Filters VIs
Requires: Adaptive Filter Toolkit
Performs adaptive linear prediction by estimating the autoregressive (AR) model of an input signal. Wire data to the signal input to determine the polymorphic instance to use or manually select the instance.
Use the pulldown menu to select an instance of this VI.
reset? specifies whether to reset the internal states and coefficients of the adaptive filter to zeroes. The default is FALSE.  
adaptive filter in specifies the adaptive filter that you create. You must specify a realvalued adaptive filter for this parameter. This VI returns errors if you wire a complexvalued adaptive filter to this parameter.  
signal specifies the signal you want this VI to process.  
error in describes error conditions that occur before this node runs. This input provides standard error in functionality.  
step size specifies the step size for the adaptive filter. If this value is less than zero, this VI ignores this parameter and uses the step size that you specify when you create the adaptive filter. If this value is zero, this VI processes the input signal without updating the coefficients of the adaptive filter. If this value is greater than zero, this VI uses this value as the step size to update the coefficients of the adaptive filter. The default is –1.


adaptive filter out returns the adaptive filter in unchanged.  
prediction error returns the prediction error e(n).  
error out contains error information. This output provides standard error out functionality.  
AR coefficients returns the coefficients of the autoregressive (AR) model this VI estimates. 
reset? specifies whether to reset the internal states and coefficients of the adaptive filter to zeroes. The default is FALSE.  
adaptive filter in specifies the adaptive filter that you create. You must specify a realvalued adaptive filter for this parameter. This VI returns errors if you wire a complexvalued adaptive filter to this parameter.  
signal specifies the signal you want this VI to process.  
error in describes error conditions that occur before this node runs. This input provides standard error in functionality.  
step size specifies the step size for the adaptive filter. If this value is less than zero, this VI ignores this parameter and uses the step size that you specify when you create the adaptive filter. If this value is zero, this VI processes the input signal without updating the coefficients of the adaptive filter. If this value is greater than zero, this VI uses this value as the step size to update the coefficients of the adaptive filter. The default is –1.


adaptive filter out returns the adaptive filter in unchanged.  
prediction error returns the prediction error e(n).  
error out contains error information. This output provides standard error out functionality.  
AR coefficients returns the coefficients of the autoregressive (AR) model this VI estimates. 
reset? specifies whether to reset the internal states and coefficients of the adaptive filter to zeroes. The default is FALSE.  
adaptive filter in specifies the adaptive filter that you create. You must specify a realvalued adaptive filter for this parameter. This VI returns errors if you wire a complexvalued adaptive filter to this parameter.  
signal specifies the signal you want this VI to process.  
error in describes error conditions that occur before this node runs. This input provides standard error in functionality.  
step size specifies the step size for the adaptive filter. If this value is less than zero, this VI ignores this parameter and uses the step size that you specify when you create the adaptive filter. If this value is zero, this VI processes the input signal without updating the coefficients of the adaptive filter. If this value is greater than zero, this VI uses this value as the step size to update the coefficients of the adaptive filter. The default is –1.


adaptive filter out returns the adaptive filter in unchanged.  
prediction error returns the prediction error e(n).  
error out contains error information. This output provides standard error out functionality.  
AR coefficients returns the coefficients of the autoregressive (AR) model this VI estimates. 
Refer to the Use Adaptive Filter for Linear Prediction VI in the labview\examples\Adaptive Filters\Getting Started directory for an example of using the AFT Linear Prediction VI.