setwelch | R Documentation |
Prepares a matrix for estimation of power spectrum via Welch's method. Also, is can be used for spectrogram.
setwelch(X, win = min(80, floor(length(X)/10)),
inc = min(24, floor(length(X)/30)), coef = 64, wintaper=0.05)
X |
Time series vector |
win |
window length |
inc |
increment |
coef |
coefficient for fft |
wintaper |
percent taper window taper |
List:
values |
Matrix of fft's staggered along the trace |
windowsize |
window length used |
increment |
increment used |
wintaper |
percent taper window taper |
originally written by Andreas Weingessel, modified Jonathan M. Lees<jonathan.lees@unc.edu>
Welch, P.D. (1967) The use of Fast Fourier Transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms IEEE Trans. Audio Electroacoustics 15, 70-73.
stft
dt <- 0.001
t <- seq(0, 6, by=dt)
x <- 6*sin(2*pi*50*t) + 10* sin(2*pi*120*t)
y <- x + rnorm(length(x), mean=0, sd=10)
plot(t,y, type='l')
title('sin(2*pi*50*t) + sin(2*pi*120*t)+ rnorm')
Y <- fft(y)
Pyy <- Y * Conj(Y)
N <- length(y)
n <- length(Pyy)/2
Syy <- (Mod(Pyy[1:n])^2)/N
fn <- 1/(2*dt)
f <- (0:(length(Syy)-1))*fn/length(Syy)
plot(f, Syy, type='l', log='y' , xlim=c(0, 150));
abline(v=c(50, 120),col='blue', lty=2)
plot(f, Syy, type='l', log='y' , xlim=c(0, 150));
abline(v=c(50, 120),col='blue', lty=2)
win <- 1024
inc <- min(24, floor(length(y)/30))
coef <- 2048
w <- setwelch(y, win=win, inc=inc, coef=coef, wintaper=0.2)
KK <- apply(w$values, 2, FUN="mean")
fw <- seq(from=0, to=0.5, length=coef)/(dt)
plot(fw, KK^2, log='', type='l' , xlim=c(0, 150)) ;
abline(v=c(50, 120), col='blue', lty=2)
Wyy <- (KK^2)/w$windowsize
plot(f, Syy, type='l', log='y' , xlim=c(0, 150))
lines(fw,Wyy , col='red')
DBSYY <- 20*log10(Syy/max(Syy))
DBKK <- 20*log10(Wyy/max(Wyy))
plot(f, DBSYY, type='l' , xlim=c(0, 150), ylab="Db", xlab="Hz")
lines(fw, DBKK, col='red')
title("Compare simple periodogam with Welch's Method")
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