Corrélation et convolution
Corrélation croisée, autocorrélation, covariance croisée, autocovariance, convolution linéaire et circulaire
Signal Processing Toolbox™ propose une famille de fonctions de corrélation et de convolution permettant de détecter les similitudes entre des signaux. Déterminez la périodicité, repérez un signal d’intérêt dissimulé dans un long enregistrement de données et mesurez les retards entre les signaux pour les synchroniser. Calculez la réponse d’un système linéaire invariant (LTI) à un signal d’entrée et effectuez des multiplications polynomiales et des convolutions circulaires.
Fonctions
Rubriques
Applications courantes
- 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. - Recaler des signaux ayant des heures de début différentes
Synchroniser les données collectées par différents capteurs à différents 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.
Autocorrélation et corrélation croisée
- 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.