Difference between revisions of "Adaptive Algorithm"
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Revision as of 15:26, 8 April 2020
Creates an Adaptive Algorithm object to be used in Linear_Equalizer or Decision_Feedback_Equalizer to define how the error signal is calculated and how taps are updated, depending on the specified algorithm
Parameters
(R): Runtime adjustable
 Algorithm Type
 enum to specify which adaptive algorithm will be used; LMS, NLMS, CMA are the valid choices
 Digital Constellation Object
 A Constellation_Object which specifies the modulation used to adapt using decision directed mode of the equalizer
 Step Size
 Specifies how quickly the adaptive algorithm will converge. Too high and the equalizer becomes unstable. The optimal value is dependent on the statistical properties of the input signal
 Modulus
 (CMA only) Specifies the number of constellation points, e.g. for QPSK modulus = 4
Example Flowgraph
See Linear_Equalizer for a flowgraph utilizing the Adaptive Algorithm Object