Correlazione e convoluzione
Correlazione incrociata, autocorrelazione, covarianza incrociata, autocovarianza, convoluzione lineare e circolare
Signal Processing Toolbox™ fornisce una famiglia di funzioni di correlazione e convoluzione che consentono di rilevare le somiglianze del segnale. Determina la periodicità, trova un segnale di interesse nascosto in un lungo record di dati e misura i ritardi tra i segnali per sincronizzarli. Calcola la risposta di un sistema lineare tempo-invariante (LTI) a un segnale di ingresso, esegui la moltiplicazione polinomiale e la convoluzione circolare.
Funzioni
Argomenti
Applicazioni comuni
- 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.
Autocorrelazione e correlazione incrociata
- 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.


