Smoothing and Denoising
Remove unwanted spikes, trends, and outliers from a signal. Smooth signals using Savitzky-Golay filters, moving averages, moving medians, linear regression, or quadratic regression.
|Visualize and compare multiple signals and spectra
|Remove polynomial trend
|Detect and replace outliers in data
|Outlier removal using Hampel identifier
|Find outliers in data
|1-D median filtering
|Moving median absolute deviation
|Savitzky-Golay filter design
|Smooth noisy data
- 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.