stft {gsignal}

Short-Term Fourier Transform

Description

Compute the short-term Fourier transform of a vector or matrix.

Usage

stft(
  x,
  window = nextpow2(sqrt(NROW(x))),
  overlap = 0.75,
  nfft = ifelse(isScalar(window), window, length(window)),
  fs = 1
)

Arguments

x

input data, specified as a numeric or complex vector or matrix. In case of a vector it represents a single signal; in case of a matrix each column is a signal.

window

If window is a vector, each segment has the same length as window and is multiplied by window before (optional) zero-padding and calculation of its periodogram. If window is a scalar, each segment has a length of window and a Hamming window is used. Default: nextpow2(sqrt(length(x))) (the square root of the length of x rounded up to the next power of two). The window length must be larger than 3.

overlap

segment overlap, specified as a numeric value expressed as a multiple of window or segment length. 0 <= overlap < 1. Default: 0.5.

nfft

Length of FFT, specified as an integer scalar. The default is the length of the window vector or has the same value as the scalar window argument. If nfft is larger than the segment length, (seg_len), the data segment is padded nfft - seg_len zeros. The default is no padding. Nfft values smaller than the length of the data segment (or window) are ignored. Note that the use of padding to increase the frequency resolution of the spectral estimate is controversial.

fs

sampling frequency (Hertz), specified as a positive scalar. Default: 1.

Value

A list containing the following elements:

f

vector of frequencies at which the STFT is estimated. If x is numeric, power from negative frequencies is added to the positive side of the spectrum, but not at zero or Nyquist (fs/2) frequencies. This keeps power equal in time and spectral domains. If x is complex, then the whole frequency range is returned.

t

vector of time points at which the STFT is estimated.

s

Short-time Fourier transform, returned as a matrix or a 3-D array. Time increases across the columns of s and frequency increases down the rows. The third dimension, if present, corresponds to the input channels.

Author(s)

Andreas Weingessel, [e-mail].
Conversion to R by Geert van Boxtel, [e-mail].

Examples

fs <- 8000
y <- chirp(seq(0, 5 - 1/fs, by = 1/fs), 200, 2, 500, "logarithmic")
ft <- stft (y, fs = fs)
filled.contour(ft$t, ft$f, t(ft$s), xlab = "Time (s)",
               ylab = "Frequency (Hz)")