Design low-pass filters using MATLAB

A low-pass filter is a filter that allows signals below a cutoff frequency (known as the passband) and attenuates signals above the cutoff frequency (known as the stopband). By removing some frequencies, the filter creates a smoothing effect. That is, the filter produces slow changes in output values to make it easier to see trends and boost the overall signal-to-noise ratio with minimal signal degradation.

Low-pass filters, especially moving average filters or Savitzky-Golay filters, are often used to clean up signals, remove noise, perform data averaging, design decimators and interpolators, and discover important patterns.

Other common design methods for low-pass FIR-based filters include Kaiser window, least squares, and equiripple.  Design methods for IIR-based filters include Butterworth, Chebyshev (Type-I and Type-II), and elliptic.

For more information on filter design, including these methods, see Signal Processing Toolbox™ for use with MATLAB®. Of particular interest is the built-in filter visualization tool, which you can use to visualize, compare, and analyze different filter responses.

Filter design assistant in Signal Processing Toolbox, for designing filters and generating MATLAB code.

See also: GPUs for signal processing algorithms in MATLAB, Savitzky-Golay filtering, median filtering, DSP System Toolbox, high-pass filter, Filter Design