A RetroSearch Logo

Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Search Query:

Showing content from https://python-control.readthedocs.io/en/stable/generated/control.correlation.html below:

Website Navigation


control.correlation — Python Control Systems Library 0.10.2 documentation

control.correlation
control.correlation(T, X, Y=None, squeeze=True)[source]

Compute the correlation of time signals.

For a time series X(t) (and optionally Y(t)), the correlation() function computes the correlation matrix E(X’(t+tau) X(t)) or the cross-correlation matrix E(X’(t+tau) Y(t)]:

tau, Rtau = correlation(T, X[, Y])

The signal X (and Y, if present) represent a continuous or discrete-time signal sampled at times T. The return value provides the correlation Rtau between X(t+tau) and X(t) at a set of time offsets tau.

Parameters:
T1D array_like

Sample times for the signal(s).

X1D or 2D array_like

Values of the signal at each time in T. The signal can either be scalar or vector values.

Y1D or 2D array_like, optional

If present, the signal with which to compute the correlation. Defaults to X.

squeezebool, optional

If True, squeeze Rtau to remove extra dimensions (useful if the signals are scalars).

Returns:
tauarray

Array of time offsets.

Rtauarray

Correlation for each offset tau.


RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4