R: Evolutive Auto-Regressive Spectrum

evolAR {RSEIS} | R Documentation

## Evolutive Auto-Regressive Spectrum

### Description

Time varying Auto-Regressive Spectrum (Gabor Transform)

### Usage

    evolAR(a, dt = 0, numf = 1024, pord = 100, Ns = 0, Nov = 0, fl = 0, fh = 10)

### Arguments

`a` | signal
`dt` | sample rate interval (s)
`numf` | Number of frequencies
`pord` | Order for Auto-regressive calculation
`Ns` | Number of sample in sub-window
`Nov` | Number of sample to overlap
`fl` | low frequency to display
`fh` | high frequency to display

### Details

This is a spectrogram function similar to the Gabor Transform but uses the Auto-Regressive method for spectrum estimation.

### Value

List

`sig` | input signal
`dt` | deltat
`wpars` | input parameters
`DSPEC` | spectrum image
`freqs` | output frequencies (y axis)
`tims` | output times (x-axis)

### Author(s)

Jonathan M. Lees<jonathan.lees@unc.edu>

### See Also

evolfft, evolMTM, MTM.drive, GETARAIC

### Examples

    data(KH)
    ###   swig(KH)

    Xamp <- KH$JSTR[[1]]

    dt <- KH$dt[1]
    plot(seq(from=0, length=length(Xamp), by=dt), Xamp, type='l')
    ##  limit the trace, somewhat
    Xamp <- Xamp[12670:22669]
    plot(seq(from=0, length=length(Xamp), by=dt), Xamp, type='l')

    Nfft<-1024   ###  fft length
    Ns<-512      ###  number of samples in a window
    Nov<-480    ###  number of samples of overlap per window
    fl<-0        ###  low frequency to return
    fh<-12     ###  high frequency to return

    EV <- evolAR(Xamp, dt = dt, numf =Nfft , pord = 100, Ns = Ns,
           Nov = Nov, fl = fl, fh = fh)

    PE <- plotevol(EV, log=1, fl=0.01, fh=fh,
          col=rainbow(100), ygrid=FALSE,
          STAMP="", STYLE="ar")

[Package RSEIS version 3.7-4 Index]