All sorts of physical processes in this analog world exhibit some degree of randomness. Think of noise, for example. Many noisy processes are described by Gaussian probability distributions. We should ...

Continuous Variable: can take on any value between two specified values. Obtained by measuring. Covariance: a measure of the direction of the linear relationship between two variables. Discrete ...

Where \(X\) is a normally distributed random variable with mean \(\mu\) and standard deviation \(\sigma\). The peak of the curve occurs at \(x=\mu\), and the spread ...

Continuous Variable: can take on any value between two specified values. Obtained by measuring. Discrete Variable: not continuous variable (cannot take on any value between two specified values).

Abstract: Bit-error probability (BEP) of a digital communication system subjected to interference can be approximately derived from the amplitude probability ...

Impact Statement: R-convolution graph kernels compare graphs without taking into account the distributions of substructures within and across graphs, leading to inaccurate graph similarity.