# Define a discretized Gaussian information source
x <- seq(from = -10, to = 10, length.out = 100)
Px <- dnorm(x, mean = 0, sd = 3)
Px <- Px / sum(Px) # Ensure that probability sums to 1
y <- x # The destination alphabet is the same as the source
# Define a quadratic cost function
cost.function <- function(x, y) {
(y - x)^2
}
# Slope of the rate-distortion curve
s <- -1
# Compute the rate-distortion value at the given point s
channel <- BlahutAlgorithm(x, Px, y, cost.function, s)
# Compute the information rate for this channel assuming a different (uniform) source distribution
uniform.dist <- rep(1 / 100, 100)
MutualInformation(channel, uniform.dist)
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