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6.22.3.1 acf
Syntax:
Input Arguments:
- cin core object
- m fft-length
acf calculates the autocorrelation function of cin via fft of length m.
6.22.3.2 amutual2
Syntax:
Input Arguments:
- cin core object
- len maximal lag
amutual2 calculates the mutual information of a time series against itself, with increasing lag uses equidistant partitioning to compute histograms.
6.22.3.3 compare
Syntax:
- compare(c1,c2, tolerance)
Input Arguments:
- c1,c2 core object of two signals
- tolerance tolerance of the signals's RMS value (default tolerance=1e-6)
compare compare two signals whether they have equal values slight differences due to rounding errors are ignored depending on the value of tolerance when signals are found to be not equal, a zero is returned.
6.22.3.4 core
core class constructor
Syntax:
Input Arguments:
A core object contains the pure data part of a signal object.
Methods: ndim dlens data
6.22.3.5 data
Syntax:
- d = data(c, varargin)
- c=core object
Input Arguments:
- varargin - selector string for data-elements in matlab notation
Return signal's data values
With no extra arguments, data returns the data array of a signal object
Another possible call is : data(signal, ':,:,1:20')
6.22.3.6 db
Syntax:
- cout = db(cin, ref, scf, dbmin)
Input Arguments:
- cin - core object
- ref - reference value
- scf - scaling factor
- dbmin - minimal db-value
compute decibel values to reference value ref and scaling factor (10 or
20) scf
6.22.3.7 diff
Syntax:
- cout = diff(cin, nth, delta)
Input Arguments:
- cin - core object
- nth - number of derivations
- delta - time difference between to signal values
nth numerical derivative along dimension 1 when data was sampled equidistantly with samplerate = 1/delta
6.22.3.8 display
Syntax:
Input Arguments:
6.22.3.9 dlens
Syntax:
Input Arguments:
returns sizes of dimensions (same as function 'size' under matlab)
6.22.3.10 embed
Syntax:
- cout = embed(cin, dim, delay, shift, windowtype)
Input Arguments:
- cin - core object
- dim - embed dimension
- delay - delay time in samples for time delay vectors
- shift - shift in samples for two sequent time delay vectors
- windowtype - type of window
Create time delay vectors with dimension dim, delay is measured in samples
The input must be a scalar time series
The result is a n by dim array, each row contains the coordinates
of one point
6.22.3.11 filterbank
Syntax:
- filterbank(cin,H,G,ORDER,BASIS)
Input Arguments:
- H - lowpass filter
- G - highpass filter
- ORDER - indicates the type of tree:
- 0 - band sorting according to the filter bank
- 1 - band sorting according to the frequency decomposition
- BASIS - desired subband decomposition
calculates the Wavelet Packet Transform of cin. It can be obtained using a selection algorithm function. It may be switched from one format to another using CHFORMAT. The different bands are sorted according to ORDER and BASIS. If BASIS is omitted, the output is a matrix with the coefficients obtained from all the wavelet packet basis in the library. Each column in the matrix represents the outputs for a level in the tree. The first column is the original signal. If the length of X is not a power of 2, the columns are zero padded to fit the different lengths. Run the script 'BASIS' for help on the basis format.
See also: IWPK, CHFORMAT, PRUNEADD, PRUNENON, GROWADD, GROWNON.
6.22.3.12 int
Syntax:
Input Arguments:
- cin - core object
- delta - time period between two data samples
numerical integration along dimension 1 when data was sampled equidistantly with samplerate = 1/delta
6.22.3.13 intermutual
Syntax:
Input Arguments:
Calculates the mutual information of cin1 and cin2.
6.22.3.14 isempty
Syntax:
Input Arguments:
test if core contains no (valid) data
6.22.3.15 medianfilt
Syntax:
Input Arguments:
moving median filter
6.22.3.16 minus
Syntax:
Input Arguments:
subtract c2 from each columns of c1
6.22.3.17 movav
Syntax:
Input Arguments:
- cin - core object
- len - average length
moving average
6.22.3.18 multires
Syntax:
- multires(cin,h,rh,g,rg,sc)
Input Arguments:
6.22.3.19 ndim
Syntax:
Input Arguments:
return number of dimensions, a scalar value has 0 dimensions
6.22.3.20 norm1
Syntax:
- cout = norm1(cin,low,upp)
Input Arguments:
- cin - core object
- low - column number
- upp - column number
normalize each single column of a the core object to be within
low,upp
6.22.3.21 norm2
Syntax:
Input Arguments:
normalize signal by removing it's mean and dividing by the standard deviation
6.22.3.22 plus
Syntax:
Input Arguments:
add c2 to each columns of c1
6.22.3.23 rang
Syntax:
Input Arguments:
6.22.3.24 rms
Syntax:
Input Arguments:
compute root mean square value of each column of c1
6.22.3.25 scalogram
Syntax:
- cout = scalogram(cin, smin, smax, sstep, tim)
6.22.3.26 spec
Syntax:
Input Arguments:
compute power spectrum for real valued signals
6.22.3.27 spec2
Syntax:
- cout = spec2(cin, fensterlen, fenster, vorschub)
Input Arguments:
- cin - core object
- fensterlen - window size
- fenster - type of window
- vorschub - moving step
spectrogramm of data using short time fft
6.22.3.28 surrogate1
Syntax:
Input Arguments:
create surrogate data for a scalar time series by randomizing phases of fourier spectrum
see : James Theiler et al.'Using Surrogate Data to Detect Nonlinearity in Time Series', APPENDIX : ALGORITHM I
6.22.3.29 surrogate2
Syntax:
Input Arguments:
create surrogate data for a scalar time series
see : James Theiler et al.'Using Surrogate Data to Detect Nonlinearity in Time Series', APPENDIX : ALGORITHM II
6.22.3.30 surrogate3
Syntax:
Input Arguments:
create surrogate data for a scalar time series
by permuting samples randomly
6.22.3.31 uminus
Syntax:
Input Arguments:
negate time series
6.22.3.32 vertcat
Syntax:
Input Arguments:
catenate two timeseries verticaly
Next: 6.23 Class achse
Up: 6.22 Class core
Previous: 6.22.2 Attributes
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