Lissage et débruitage
Supprimez les pics indésirables, les tendances et les valeurs aberrantes d’un signal. Lissez les signaux avec des filtres de Savitzky-Golay, des moyennes ou médianes mobiles, ou des régressions linéaires ou quadratiques.
Applications
| Signal Analyzer | Visualiser et comparer plusieurs signaux et spectres |
Fonctions
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 |
Rubriques
- 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.
Sélection d՚exemples
Signal Smoothing
Discover important patterns in your data while leaving out noise, outliers, and other irrelevant information.
Design and Analyze Savitzky-Golay Filters
Design, analyze, and apply Savitzky-Golay smoothing and differentiation filters, include weighting and optimization for best smoothness.
