rugo {seewave}

Rugosity of a time wave

Description

This function computes the rugosity of a time wave or time series

Usage

rugo(x, ...)

Arguments

x

a vector

...

other mean parameters.

Details

The formula has been slightly modified from Mezquida & Martinez (2009: 826) to fit with the classical definition of the root-mean-square (see rms).
The rugosity is then computed as following:

rugo = \sqrt{\sum_{i=1}^{n-1} \frac{(x_{i+1}-x_{i})^2}{n}}

for a vector x of length n.

Value

A vector of length 1.

Note

The rugosity of a noisy signal will tend to be higher than that of a pure tone signal, all other things being equal.

Author(s)

Jerome Sueur

References

Mezquida DA, Martinez JL (2009) - Platform for bee-hives monitoring based on sound analysis. A perpetual warehouse for swarm's daily activity. Spanish Journal of Agricultural Research 7, 824-828.

See Also

roughness, rms, sh, th, H.

Examples

data(tico) ; tico <-tico@left
# rugosity of the original recording normalised
rugo(tico/max(tico))
# synthesis of white noise with the same duration as tico
noise <- noisew(d=length(tico)/22050, f=22050)
# tico is normalised to get similar amplitude with the noise
tico.norm <- tico/max(tico)
# addition of noise to tico
tico.noisy <- tico.norm + 0.5*noise
# new rugosity (higher) on normalised signal
rugo(tico.noisy/max(tico.noisy))