Description Usage Arguments Details Value See Also Examples

View source: R/makeFunctions.R

Compute the noise scale levels for each channel using the **S**ignal to **N**oise **R**atios

1 | ```
sigmaSNR(signal, SNR)
``` |

`signal` |
Noisefree multichannel input signal |

`SNR` |
A numeric vector specifying the desired |

The output noise scale levels (theoretical standard deviation for the process noise process in each channel) is governed by the blurred **S**ignal-to-**N**oise **R**atio (SNR) measured in decibels (dB) where,

*SNR = 10 log_{10} (\frac{||k*f||^2}{σ^2)}*

and k*f is the blurred signal, *||\cdot||* is the norm operator and *σ* is the standard deviation of the noise. Roughly speaking, noise levels are considered high, medium and low for the cases 10 dB, 20 dB and 30 dB respectively.

A numeric vector with m elements giving the scales (standard deviation of the noise in each channel) to achieve the desired SNR.

1 2 3 4 5 6 7 8 9 | ```
n <- 1024
m <- 3
signal <- makeLIDAR(n)
blur <- gammaBlur(n, c(0.5, 0.75, 1), rep(1, m))
X <- blurSignal(signal, blur)
SNR <- 10*1:3
sigma <- sigmaSNR(X, SNR)
E <- multiNoise(n, sigma)
sigmaEst <- multiSigma(E)
``` |

mwaved documentation built on July 13, 2017, 5:03 p.m.

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