Smoothing and Denoising

Savitzky-Golay smoothing, median and Hampel filtering, detrending

Remove unwanted spikes, trends, and outliers from a signal. Smooth signals using Savitzky-Golay filters, moving averages, moving medians, linear regression, or quadratic regression.

Apps

Signal Analyzer

Visualize and compare multiple signals and spectra

Functions

`detrend`	Remove polynomial trend
`filloutliers`	Detect and replace outliers in data
`hampel`	Outlier removal using Hampel identifier
`isoutlier`	Find outliers in data
`medfilt1`	1-D median filtering
`movmad`	Moving median absolute deviation
`movmedian`	Moving median
`sgolay`	Savitzky-Golay filter design
`sgolayfilt`	Savitzky-Golay filtering
`smoothdata`	Smooth noisy data

Topics

Remove Trends from Data
Take out irrelevant overall patterns that impede data analysis.
Remove the 60 Hz Hum from a Signal
Filter out 60 Hz oscillations that often corrupt measurements.
Remove Spikes from a Signal
Use median filtering to eliminate unwanted transients from data.
Reconstruct a Signal from Irregularly Sampled Data
Resample and interpolate data measured at irregular intervals.
Eliminate Outliers Using Hampel Identifier
Detect and remove outliers using a simplified implementation of the Hampel algorithm.

Featured Examples

Signal Smoothing

Discover important patterns in your data while leaving out noise, outliers, and other irrelevant information.

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New

Design and Analyze Savitzky-Golay Filters

Design, analyze, and apply Savitzky-Golay smoothing and differentiation filters, include weighting and optimization for best smoothness.

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