mexihat {gsignal} | R Documentation |
Mexicat Hat
Description
Generate a Mexican Hat (Ricker) wavelet sampled on a regular grid.
Usage
mexihat(lb = -5, ub = 5, n = 1000)
Arguments
lb , ub |
Lower and upper bounds of the interval to evaluate the wavelet on. Default: -5 to 5. |
n |
Number of points on the grid between |
Details
The Mexican Hat or Ricker wavelet is the negative normalized second derivative of a Gaussian function, i.e., up to scale and normalization, the second Hermite function. It is a special case of the family of continuous wavelets (wavelets used in a continuous wavelet transform) known as Hermitian wavelets. The Ricker wavelet is frequently employed to model seismic data, and as a broad spectrum source term in computational electrodynamics. It is usually only referred to as the Mexican hat wavelet in the Americas, due to taking the shape of a sombrero when used as a 2D image processing kernel. It is also known as the Marr wavelet (source: Wikipedia)
Value
A list containing 2 variables; x
, the grid on which the
complex Mexican Hat wavelet was evaluated, and psi
(\Psi
), the
evaluated wavelet on the grid x
.
Author(s)
Sylvain Pelissier, sylvain.pelissier@gmail.com.
Conversion to R by Geert van Boxtel, G.J.M.vanBoxtel@gmail.com.
Examples
mh <- mexihat(-5, 5, 1000)
plot(mh$x, mh$psi, type="l", main = "Mexican Hat Wavelet",
xlab = "", ylab = "")