timeScalarFeatureOptions
Store information for converting time-domain feature vectors to scalar values
Since R2024b
Description
Use a timeScalarFeatureOptions
object to store methods to convert time-domain
feature vectors to scalars. You can use the resulting timeScalarFeatureOptions
object to
set the ScalarizationMethod
property of a signalTimeFeatureExtractor
object.
Creation
Description
creates an
object opts
= timeScalarFeatureOptionsopts
that stores the scalarization methods with default values
(empty string arrays) for all signal features in time domain.
specifies scalarization methods for each time-domain signal feature using name-value
arguments. You can specify multiple name-value arguments. For example,
opts
= timeScalarFeatureOptions(Name=Value
)timeScalarFeatureOptions(PeakValue=["Mean"
"Kurtosis"],All="Skewness")
specifies "Mean"
and
"Kurtosis"
as scalarization methods for the peak value feature, and
"Skewness"
as the scalarization method for all the time-domain
features. For more information about scalarization methods, see Scalarization Methods for Domain-Specific Signal Features.
Properties
PeakValue
— Scalarization methods for peak value feature vector
strings(0)
(default) | string array | cell array
Scalarization methods for the peak value feature, specified as a string array or as a cell array of character vectors.
Each element of the array corresponds to a scalarization method that you apply on the feature, if enabled. Enable signal features for extraction when creating the signalTimeFeatureExtractor
object.
If you specify this feature, the feature extractor object:
Associates with the feature any scalarization methods you have specified for it.
Appends any scalarization methods you have specified using the
All
name-value argument.
Example: PeakValue = ["Mean" "Skewness"]
sets the option to extract the mean
and the skewness of the peak value feature vector.
Data Types: cell
| string
All
— Scalarization methods for all signal features
strings(0)
(default) | string array | cell array
Scalarization methods for all the signal features, specified as a string array or as a cell array of character vectors.
Each element of the array corresponds to a scalarization method that you apply on all the enabled features. Enable signal features for extraction when creating the feature extractor object.
If you specify All
, the feature extractor object:
Associates the scalarization methods you have specified with all enabled features.
Appends them to the list of methods already specified for each particular feature.
Example: All = ["Mean" "PeakValue"]
sets the option to extract the mean and the peak value of all the feature vectors.
Data Types: cell
| string
Examples
Add Scalarization Methods for Time-Domain Feature Extraction
Create a timeScalarFeatureOptions
object with default values.
opts = timeScalarFeatureOptions
opts = timeScalarFeatureOptions with properties: PeakValue: [0x0 string] All: [0x0 string]
Add scalarization methods for the peak value time-domain feature:
opts.PeakValue = ["Mean" "Kurtosis"];
Display the list of scalarization methods for all the time-domain features.
opts
opts = timeScalarFeatureOptions with properties: PeakValue: ["Mean" "Kurtosis"] All: [0x0 string]
Set Scalarization Method Property in Time-Domain Feature Extractor Object
Create and use a timeScalarFeatureOptions
object to set the ScalarizationMethod
property in a signalTimeFeatureExtractor
object.
Specify the standard deviation and the kurtosis as scalar features for the peak value time-domain feature. Store this information in a timeScalarFeatureOptions
object.
opts = timeScalarFeatureOptions( ... PeakValue=["StandardDeviation" "Kurtosis"]);
Create a signalTimeFeatureExtractor
object to extract the root mean square and peak value with its corresponding scalar values. Display the ScalarizationMethod
property of the feature extractor object.
tFE = signalTimeFeatureExtractor( ... RMS=true,PeakValue=true, ... ScalarizationMethod=opts); disp(tFE.ScalarizationMethod)
timeScalarFeatureOptions with properties: PeakValue: ["StandardDeviation" "Kurtosis"] All: [0x0 string]
Scalar and Vector Features in Time Domain
Set scalarization methods to convert time-domain feature vectors to scalar values.
Specify "Mean"
and "StandardDeviation"
as scalarization methods for the peak value feature. Specify "Kurtosis"
as the scalarization method for all the enabled signal features. Store this information in a timeScalarFeatureOptions
object.
opts = timeScalarFeatureOptions( ... PeakValue=["Mean" "StandardDeviation"],All="Kurtosis")
opts = timeScalarFeatureOptions with properties: PeakValue: ["Mean" "StandardDeviation"] All: "Kurtosis"
Create a signalTimeFeatureExtractor
object to extract the signal-to-noise ratio, peak value, and total harmonic distortion features. Use opts
to set the scalarization method property of the feature extractor object.
sFE = signalTimeFeatureExtractor( ... SNR=true,PeakValue=true,THD=true, ... ScalarizationMethod=opts)
sFE = signalTimeFeatureExtractor with properties: Properties FrameSize: [] FrameRate: [] SampleRate: [] IncompleteFrameRule: "drop" FeatureFormat: "matrix" Enabled Features SNR, THD, PeakValue Disabled Features Mean, RMS, StandardDeviation, ShapeFactor, SINAD, CrestFactor ClearanceFactor, ImpulseFactor
Extract vectors and scalar features from a signal. Observe the list of extracted features.
Fs = 1000; a = [1 1 0.1 0.03]; f = 60*[1 3 5 7]; t = (0:1/Fs:1)'; x = cos(2*pi*f.*t)*a'; [features,indices] = extract(sFE,x)
features = 1×6
30.4576 0.0432 2.1300 2.1300 0 NaN
indices = struct with fields:
SNR: 1
THD: 2
PeakValue: 3
PeakValueMean: 4
PeakValueStandardDeviation: 5
PeakValueKurtosis: 6
More About
Scalarization Methods for Domain-Specific Signal Features
To set the scalarization methods for features in time domain, frequency domain, or time-frequency domain, select the domain-specific feature extractor objects and scalarization method specification. Refer to the following table for the list of domain-specific features from which you can extract scalar features.
Feature domain | Feature extractor object | Scalarization method specification | Features that support scalarization |
---|---|---|---|
Time | signalTimeFeatureExtractor | timeScalarFeatureOptions object | PeakValue |
Frequency | signalFrequencyFeatureExtractor | frequencyScalarFeatureOptions object | PeakAmplitude WelchPSD |
Time-frequency | signalTimeFrequencyFeatureExtractor | timeFrequencyScalarFeatureOptions object | All time-frequency features |
For a given feature vector v with N elements, the scalarization method options convert v to a scalar s as follows.
"Mean"
— Mean, defined as the average value of v."StandardDeviation"
— Standard deviation of the elements of v, normalized by N-1."PeakValue"
— Peak value, defined as the maximum absolute value of v."Kurtosis"
— Kurtosis, defined as the ratio between the fourth moment of v and the squared second moment of v."Skewness"
— Skewness, defined as the ratio between the third moment of v and the second moment of v raised to the power of 1.5.
"ClearanceFactor"
— Clearance factor, defined as the ratio between the peak value of v and the squared mean of the square roots of the absolute values of v."CrestFactor"
— Crest factor, defined as the ratio between the peak value of v and the root-mean-square value of v."Energy"
— Energy, defined as the sum of the squared values of v."Entropy"
— Entropy, defined as the sum of plog2p values, where p is the vector of normalized squared values of v with respect to their sum.where
Note
The scalarization method
"Entropy"
is not supported for theWaveletEntropy
nor theSpectralEntropy
features."ImpulseFactor"
— Impulse factor, defined as the ratio between the peak value of v and the average absolute value of v.
Version History
Introduced in R2024b
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