Sliding short-time Fourier transform

Usage

slidingSTFT(
  sampling_rate,
  window_samples,
  hop_samples,
  n_fft = window_samples,
  window = c("hann", "hamming", "rectangular"),
  detrend = c("mean", "none"),
  output = c("power", "complex"),
  bands = NULL,
  causal_filter = NULL,
  n_features = NULL
)

Arguments

sampling_rate: Positive samples per second.
window_samples: Exact frame length.
hop_samples: Exact frame advance, no larger than the window.
n_fft: Exact FFT length, at least the frame length.
window: Exact governed window definition.
detrend: Per-frame mean removal or no detrending.
output: Return one-sided density power or normalized complex coefficients whose squared modulus equals that density.
bands: Optional uniquely named two-column Hz matrix.
causal_filter: Optional independent PhysioPreprocess::StreamFilter objects or factory.
n_features: Optional channel count to bind at construction.

Value

A mutable SlidingSTFT streaming processor.

Examples

sr <- 100
signal <- sin(2 * pi * 10 * seq_len(200) / sr)
stft <- slidingSTFT(sr, window_samples = 64L, hop_samples = 16L,
                    output = "power")
result <- update(stft, signal)
dim(result$output)
#> [1]  9 33  1