Glättung und Rauschunterdrückung
Entfernen Sie unerwünschte Spitzen, Trends und Ausreißer aus einem Signal. Glätten von Signalen mithilfe von Savitzky-Golay-Filtern, gleitenden Mittelwerten, gleitenden Medianen, linearer Regression oder quadratischer Regression.
Apps
| Signal Analyzer | Visualize and compare multiple signals and spectra |
Funktionen
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 |
Themen
- 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.
Enthaltene Beispiele
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.
