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alg = cma(stepsize)
alg = cma(stepsize,leakagefactor)
The cma function creates an adaptive algorithm object that you can use with the lineareq function or dfe function to create an equalizer object. You can then use the equalizer object with the equalize function to equalize a signal. To learn more about the process for equalizing a signal, see Adaptive Algorithms.
Note: After you use either lineareq or dfe to create a CMA equalizer object, you should initialize the equalizer object's Weights property with a nonzero vector. Typically, CMA is used with differential modulation; otherwise, the initial weights are very important. A typical vector of initial weights has a 1 corresponding to the center tap and 0s elsewhere. |
alg = cma(stepsize) constructs an adaptive algorithm object based on the constant modulus algorithm (CMA) with a step size of stepsize.
alg = cma(stepsize,leakagefactor) sets the leakage factor of the CMA. leakagefactor must be between 0 and 1. A value of 1 corresponds to a conventional weight update algorithm, while a value of 0 corresponds to a memoryless update algorithm.
The table below describes the properties of the CMA adaptive algorithm object. To learn how to view or change the values of an adaptive algorithm object, see Access Properties of an Adaptive Algorithm.
Property | Description |
---|---|
AlgType | Fixed value, 'Constant Modulus' |
StepSize | CMA step size parameter, a nonnegative real number |
LeakageFactor | CMA leakage factor, a real number between 0 and 1 |
[1] Haykin, Simon, Adaptive Filter Theory, Third Ed., Upper Saddle River, NJ, Prentice-Hall, 1996.
[2] Johnson, Richard C., Jr., Philip Schniter, Thomas. J. Endres, et al., "Blind Equalization Using the Constant Modulus Criterion: A Review," Proceedings of the IEEE, Vol. 86, October 1998, pp. 1927–1950.
dfe | equalize | lineareq | lms | normlms | rls | signlms | varlms