rkernel: Kernel for Reconstruction from Wavelet Ridges

In Rwave: Time-Frequency Analysis of 1-D Signals

Kernel for Reconstruction from Wavelet Ridges

Description

Computes the cost from the sample of points on the estimated ridge and the matrix used in the reconstruction of the original signal, in the case of real constraints. Modification of the function kernel.

Usage

rkernel(node, phinode, nvoice, x.inc=1, x.min=node[1],
x.max=node[length(node)], w0=2 * pi, plot=FALSE)

Arguments

node	values of the variable b for the nodes of the ridge.
phinode	values of the scale variable a for the nodes of the ridge.
nvoice	number of scales within 1 octave.
x.inc	step unit for the computation of the kernel.
x.min	minimal value of x for the computation of Q_2.
x.max	maximal value of x for the computation of Q_2.
w0	central frequency of the wavelet.
plot	if set to TRUE, displays the modulus of the matrix of Q_2.

Details

Uses Romberg's method for computing the kernel.

Value

matrix of the Q_2 kernel

References

See discussions in the text of "Time-Frequency Analysis".

See Also

kernel, fastkernel, gkernel, zerokernel.

Rwave documentation built on Oct. 22, 2022, 1:05 a.m.