Method ao/noisePower


  NOISEPOWER computes the noise power spectral density in a time-series as a function of time.
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  DESCRIPTION: NOISEPOWER computes the noise power spectral density in a
               time-series as a function of time. 
  
  The method takes the prescribed spectra of the input data and computes
  the mean spectral density in the specified frequency band and returns
  this for each segment that can be fit into the original time-series.
 
 
  CALL:        out = obj.noisePower(pl)
               out = noisePower(objs, pl)
 
  INPUTS:      pl      - a parameter list
               obj(s)  - input ao object(s)
 
  OUTPUTS:     out - some output.
 
 
  Created 2016-03-08, M Hewitson
 
  Parameters Description
 
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Method Details
Access public
Defining Class ao
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
psd
NFFT -1 none The number of samples in each fft [default: length of input data].
A string value containing the variable 'fs' can also be used, e.g.,
plist('Nfft', '2*fs')
WIN 'Hanning'
  • 'Rectangular'
  • 'Welch'
  • 'Bartlett'
  • 'Hanning'
  • 'Hamming'
  • 'Nuttall3'
  • 'Nuttall4'
  • 'Nuttall3a'
  • 'Nuttall3b'
  • 'Nuttall4a'
  • 'Nuttall4b'
  • 'Nuttall4c'
  • 'BH92'
  • 'SFT3F'
  • 'SFT3M'
  • 'FTNI'
  • 'SFT4F'
  • 'SFT5F'
  • 'SFT4M'
  • 'FTHP'
  • 'HFT70'
  • 'FTSRS'
  • 'SFT5M'
  • 'HFT90D'
  • 'HFT95'
  • 'HFT116D'
  • 'HFT144D'
  • 'HFT169D'
  • 'HFT196D'
  • 'HFT223D'
  • 'HFT248D'
  • 'Kaiser'
  • 'levelledHanning'
The window to be applied to the data to remove the discontinuities at edges of segments. [default: taken from user prefs]
Only the design parameters of the window object are used. Enter a string value containing the window name e.g.
plist('Win', 'Kaiser', 'psll', 200)
plist('Win', 'BH92')
PSLL 200 none The peak sidelobe level for Kaiser windows.
Note: it is ignored for all other windows
OLAP -1 none The segment percent overlap [-1 == take from window function]
ORDER, N 0
  • -1
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
The order of segment detrending:
  • -1 - no detrending
  • 0 - subtract mean
  • 1 - subtract linear fit
  • N - subtract fit of polynomial, order N
NAVS -1 none Force number of averages. If set, and if Nfft was set to 0 or -1,
the number of points for each window will be calculated to match the request.
DROP WINDOW SAMPLES 1
  • 1
  • 0
Drop the recommended (by the window) number of samples of the final computed spectral series.
TIMES, SPLIT [] none The time range to analyze. If not empty, sets the time interval to operate on.
As in ao/split, the interval can be specified by:
  • a vector of doubles
  • a timespan object
  • a cell array of time strings
  • a vector of time objects
MASK [] none Mask out segments in the averaging process. The mask should be a vector of logical values, one value per segment being averaged. The plist method [psdSegments] can be used to generate a default mask for your PSD settings. If empty, all segments will be included in the average.
SCALE 'PSD'
  • 'PSD'
  • 'ASD'
  • 'PS'
  • 'AS'
The scaling of output. Choose from:
  • PSD - Power Spectral Density
  • ASD - Amplitude (linear) Spectral Density
  • PS - Power Spectrum
  • AS - Amplitude (linear) Spectrum
noisePower
FREQUENCIES, FREQS, F [0 Inf] none The frequency interval over which to average. Specify a vector [f1 f2].
TOTAL POWER, TOT PWR 0
  • 0
  • 1
Scale to be total power (mulitply by bandwidth).
BINS 1 none Select every nth bin in the averaging.

Example

plist('NFFT', [-1], 'WIN', 'Hanning', 'PSLL', [200], 'OLAP', [-1], 'ORDER', [0], 'NAVS', [-1], 'DROP WINDOW SAMPLES', [true], 'TIMES', [[]], 'MASK', [[]], 'SCALE', 'PSD', 'FREQUENCIES', [[0 Inf]], 'TOTAL POWER', [false], 'BINS', [1])

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Some information of the method ao/noisePower are listed below:
Class name ao
Method name noisePower
Category Signal Processing
Package name ltpda
Can be used as modifier 1
Supported numeric types {'double'}




©LTP Team