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DTW Barycenter Averaging (DBA)

Source: R/ops-dtw.R
dtwAverage.Rd

Computes the average waveform using DTW Barycenter Averaging, which accounts for time warping in the averaging process.

Usage

dtwAverage(x, init = "medoid", max_iter = 30, tol = 1e-04, window_size = NULL)

Arguments

x

A PhysioExperiment object or matrix (time x observations).

init

Initial reference: "medoid", "mean", or a numeric vector.

max_iter

Maximum iterations for DBA.

tol

Convergence tolerance.

window_size

Sakoe-Chiba band width.

Value

A list containing:

average

The DTW-averaged waveform

iterations

Number of iterations used

alignments

List of alignment paths to the average

References

Sakoe H, Chiba S (1978). "Dynamic programming algorithm optimization for spoken word recognition." IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43-49.

Petitjean F, Ketterlin A, Gancarski P (2011). "A global averaging method for dynamic time warping, with applications to clustering." Pattern Recognition, 44(3), 678-693.

See also

dtwDistance(), dtwDistanceMatrix(), dtwClustering()

Examples

# Average multiple gait cycles with timing variation
set.seed(123)
t <- seq(0, 100, length.out = 100)
data <- sapply(1:20, function(i) {
  phase <- rnorm(1, 0, 10)
  sin(2 * pi * (t + phase) / 100) * 30 + rnorm(100, 0, 2)
})

avg <- dtwAverage(data)
plot(avg$average, type = "l")