Learn R Programming

gasper (version 1.1.1)

HPFVN: High Pass Filter Von Neumann Estimator.

Description

Graph extension of the Von Neummann variance estimator using finest scale coefficients.

Usage

HPFVN(wcn, evalues, b)

Arguments

wcn

Noisy wavelet coefficients.

evalues

Laplacian spectrum.

b

Parameter that control the number of scales.

References

von Neumann, J. (1941). Distribution of the ratio of the mean square successive difference to the variance. Ann. Math. Statistics, 35(3), 433--451.

de Loynes, B., Navarro, F., Olivier, B. (2021). Data-driven thresholding in denoising with Spectral Graph Wavelet Transform. Journal of Computational and Applied Mathematics, Vol. 389.

Examples

Run this code
# NOT RUN {
matrixname <- "grid1"
groupname <- "AG-Monien"
graph <- download_graph(matrixname,groupname)
A <- graph$sA
L <- laplacian_mat(A)
n <- nrow(L)
val1 <- eigensort(L)
evalues <- val1$evalues
evectors <- val1$evectors
lmax <- max(evalues)
f <- randsignal(eta=0.01,k=5,A=A)
sigma <- 0.1
noise <- rnorm(n, sd = sigma)
y <- f + noise
b <- 2
wcn <- forward_sgwt(y, evalues, evectors, b=b)
HPFVN(wcn, evalues, b)
# }

Run the code above in your browser using DataLab