evolAR | R Documentation |
Time varying Auto-Regressive Spectrum (Gabor Transform)
evolAR(a, dt = 0, numf = 1024, pord = 100, Ns = 0, Nov = 0, fl = 0, fh = 10)
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 |
This is a spectrogram function similar to the Gabor Transform but uses the Auto-Regressive method for spectrum estimation.
List
sig |
input signal |
dt |
deltat |
wpars |
input parameters |
DSPEC |
spectrum image |
freqs |
output frequencies (y axis) |
tims |
output times (x-axis) |
Jonathan M. Lees<jonathan.lees@unc.edu>
evolfft, evolMTM, MTM.drive, GETARAIC
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")
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