Reconstruct Phase Space
Reconstruct phase space of a uniformly sampled signal in the Live Editor
Description
The Reconstruct Phase Space task lets you interactively reconstruct phase space of a uniformly sampled signal. The task automatically generates MATLAB® code for your live script. For more information about Live Editor tasks generally, see Add Interactive Tasks to a Live Script.
Phase space reconstruction is useful to verify the system order and reconstruct all
dynamic system variables, while preserving system properties. Reconstructing the phase space
is performed when limited data is available, or when the phase space dimension and lag values
are unknown. Also, the nonlinear features approximateEntropy
, correlationDimension
, and lyapunovExponent
use phase space reconstruction as the first step of the
computation. For more information about phase space reconstruction, see phaseSpaceReconstruction
.
Open the Task
To add the Reconstruct Phase Space task to a live script in the MATLAB Editor:
On the Live Editor tab, select Task > Reconstruct Phase Space.
In a code block in your script, type a relevant keyword, such as
phase
orphase space
. SelectReconstruct Phase Space
from the suggested command completions.
Examples
Related Examples
Parameters
Select SignalSignal
— Uniformly sampled time-domain signal
array | timetable
Select a uniformly sampled time-domain signal in array or timetable format.
Time Lag
— Check to use Average Mutual Information (AMI) algorithm to compute time lag
on (default) | off
Check to use Average Mutual Information (AMI) algorithm to compute time lag. Clear to try your own value of Maximum Lag and Histogram Bins. If the time delay is too small, random noise is introduced in the states. In contrast, if the lag is too large, the reconstructed dynamics do not represent the true dynamics of the time series.
Maximum Lag
— Maximum value of lags used in the lag estimation
positive scalar
Maximum value of lag used to estimate the time delay using the Average Mutual Information (AMI) algorithm.
Histogram Bins
— Number of bins for discretization when computing the average mutual information
positive scalar
Number of bins for discretization to compute lag using the AMI algorithm. Set the value of Histogram Bins based on the length of your signal.
Embedding Dimension
— Check to use Percent False Neighbors (PFN) algorithm to compute embedding dimension
on (default) | off
Check to use Percent False Neighbors (PFN) algorithm to automatically compute embedding dimension.
Maximum Dimension
— Maximum value of embedding dimension used in the dimension estimation
positive scalar
Maximum value of embedding dimension used in the dimension estimation with Percent False Neighbors (PFN) algorithm.
Distance Threshold
— Distance ratio threshold for determining two points as false neighbors
scalar
Distance ratio threshold for determining two points as false neighbors using Percent
False Neighbors (PFN) algorithm. For more information, see phaseSpaceReconstruction
.
Percent False Neighbors
— Percent false neighbors threshold for detecting embedding dimension
scalar
Percent false neighbors threshold for detecting embedding dimension using PFN
algorithm. To specify percent false neighbors, check the Embedding
Dimension check box. For more information, see phaseSpaceReconstruction
.
Output Plot
— Number of output plots to display
Individual
(default) | All
| None
Number of output plots to display. To toggle between the reconstructed plot and the
histogram plot, and to go through each plot, select
Individual
. To display both plots in the Live Editor,
select All
. To hide plots, select
None
.
Version History
Introduced in R2019b