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Compute RMS of sample blocks

Source: R/block_rms.R
block_rms.Rd

This function is used to compute the RMS (root-mean-square) of successive blocks of samples.

Usage

block_rms(X, n, nov = NULL)

Arguments

X

A vector or a matrix containing samples of a signal in each column.

n

The number of samples from X to use in each analysis block.

nov

The number of samples that the next block overlaps the previous block.

Value

A list with 2 elements:

  • Y: A vector or matrix containing the RMS value of each block. If X is a mxn matrix, Y is pxn where p is the number of complete n-length blocks with nov that can be made out of m samples, i.e., n+(p-1)*(n-nov) < m

  • samples: The time at which each output in Y is reported, in units of samples of X. So if samples[1] = 12, then the value Y[1] corresponds to the “time” 12 samples in X. The times at which Y values are reported are the centers of the averaging windows.

Note

Output sampling rate is the same as the input sampling rate so s and v have the same size as p.

Frame: This function assumes a [north,east,up] navigation frame and a [forward,right,up] local frame. In these frames, a positive pitch angle is an anti-clockwise rotation around the y-axis. A descending animal will have a negative pitch angle.

Examples

X <- matrix(c(1:20), byrow = TRUE, nrow = 4)
block_rms(X, n = 2, nov = NULL)
#> $Y
#>           [,1]      [,2]      [,3]      [,4]      [,5]
#> [1,]  4.301163  5.147815  6.041523  6.964194  7.905694
#> [2,] 13.729530 14.713939 15.700318 16.688319 17.677670
#> 
#> $samples
#> [1] 1 3
#>