Korrelation und Faltung (Convolution)
Kreuzkorrelation, Autokorrelation, Kreuzkovarianz, Autokovarianz, lineare und zirkuläre Faltung
Signal Processing Toolbox™ bietet eine Familie von Korrelations- und Faltungsfunktionen, mit denen Sie Signalähnlichkeiten erkennen können. Periodizität bestimmen, ein interessantes Signal in einem langen Datensatz finden und Verzögerungen zwischen Signalen messen, um diese zu synchronisieren. Berechnen Sie die Antwort eines linearen zeitinvarianten (LTI) Systems auf ein Eingangssignal, führe eine Polynommultiplikation durch und führe eine zirkuläre Faltung durch.
Funktionen
Themen
Gängige Anwendungen
- Find a Signal in a Measurement
Determine if a signal matches a segment of a noisy longer stream of data. - Align Two Simple Signals
Learn to align signals of different lengths using cross-correlation. - Align Signals with Different Start Times
Synchronize data collected by different sensors at different instants. - Align Signals Using Cross-Correlation
Use cross-correlation to fuse asynchronous data. - Find Periodicity Using Autocorrelation
Verify the presence of cycles in a noisy signal, and determine their durations. - Echo Cancellation
Use autocorrelation to filter out an echo from a speech recording.
Autokorrelation und Kreuzkorrelation
- Cross-Correlation with Multichannel Input
Compute autocorrelations and cross-correlations of a multichannel signal. - Confidence Intervals for Sample Autocorrelation
Create confidence intervals for the autocorrelation sequence of a white noise process. - Autocorrelation Function of Exponential Sequence
Compute the autocorrelation of an exponential sequence and compare it to the analytic result. - Cross-Correlation of Two Exponential Sequences
Compute the cross-correlation of two exponential sequences and compare it to the analytic result. - Autocorrelation of Moving Average Process
Use filtering to introduce autocorrelation into a white noise process. - Cross-Correlation of Two Moving Average Processes
Find and plot the cross-correlation sequence between two moving average processes. - Cross-Correlation of Delayed Signal in Noise
Use the cross-correlation sequence to detect the time delay in a noise-corrupted sequence. - Cross-Correlation of Phase-Lagged Sine Wave
Use the cross-correlation sequence to estimate the phase lag between two sine waves. - Linear and Circular Convolution
Establish an equivalence between linear and circular convolution.


