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System object: dsp.BlockLMSFilter
Package: dsp

Filter inputs using Block LMS algorithm


[Y,ERR,WTS] = step(blms,X,D)
[Y,ERR] = step(blms,X,D)
[...] = step(blms,X,D,MU)
[...] = step(blms,X,D,A)
[...] = step(blms,X,D,R)
[Y,ERR,WTS] = step(blms,X,D,MU,A,R)



Starting in R2016b, instead of using the step method to perform the operation defined by the System object™, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.

[Y,ERR,WTS] = step(blms,X,D) filters the input X, using D as the desired signal, and returns the filtered output in Y. The filter error is in ERR, and the estimated filter weights is in WTS. The filter weights update once for every block of data that the object processes.

[Y,ERR] = step(blms,X,D) returns only the filtered output in Y and the filter error in ERR, when the WeightsOutputPort property is false.

[...] = step(blms,X,D,MU) uses MU as the step size, when you set the StepSizeSource property to Input port.

[...] = step(blms,X,D,A) uses A as the adaptation control, when you set the AdaptInputPort property to true. When A is nonzero, the filter continuously updates the filter weights. When A is zero, the filter weights remain constant.

[...] = step(blms,X,D,R) uses R as a reset signal, when you set the WeightsResetInputPort property to true. Use the WeightsResetCondition property to set the reset trigger condition. If a reset event occurs, the filter resets the filter weights to their initial values.

[Y,ERR,WTS] = step(blms,X,D,MU,A,R) filters input X, using D as the desired signal, MU as the step size, A as the adaptation control, and R as the reset signal. The objects returns the filtered output in Y, the filter error in ERR, and the adapted filter weights in WTS. Set the properties appropriately to provide all possible inputs.


obj specifies the System object on which to run this step method.

The object performs an initialization the first time the step method is executed. This initialization locks nontunable properties (MATLAB) and input specifications, such as dimensions, complexity, and data type of the input data. If you change a nontunable property or an input specification, the System object issues an error. To change nontunable properties or inputs, you must first call the release method to unlock the object.

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