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Median Filter

Median filter

  • Median Filter block

DSP System Toolbox / Filtering / Filter Designs
DSP System Toolbox / Statistics


The Median Filter block computes the moving median of the input signal along each channel independently over time. The block uses the sliding window method to compute the moving median. In this method, a window of specified length moves over each channel sample by sample, and the block computes the median of the data in the window. This block performs median filtering on the input data over time. For more details, see Algorithms.



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Data over which the block computes moving median. The block accepts real-valued or complex-valued multichannel inputs, that is, m-by-n size inputs, where m ≥ 1, and n ≥ 1. The block also accepts variable-size inputs. During simulation, you can change the size of each input channel. However, the number of channels cannot change.

Data Types: single | double
Complex Number Support: Yes


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The size of the moving median output matches the size of the input. The block uses the sliding window method to compute the moving median. For more details, see Algorithms.

Data Types: single | double
Complex Number Support: Yes


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Window length specifies the length of the sliding window in samples.

Specify the type of simulation to run as one of the following:

  • Code generation –– Simulate model using generated C code. The first time you run a simulation, Simulink® generates C code for the block. The C code is reused for subsequent simulations, as long as the model does not change. This option requires additional startup time but provides faster simulation speed than Interpreted execution.

  • Interpreted execution –– Simulate model using the MATLAB®  interpreter. This option shortens startup time but has slower simulation speed than Code generation.

Block Characteristics

Data Types

double | single

Multidimensional Signals


Variable-Size Signals



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Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced in R2016b