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

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