pvl(i) = exp( -(1/2) * (v-muDATA)*icmDATA*(v-muDATA)' ) / ( (2*pi)^(D/2) * (det(cmDATA))^(1/2) )

This expression represents the probability density function (PDF) of a multivariate normal distribution, where "pvl" stands for "probability value at location i", "exp" is the exponential function, "v" is a vector of random variables, "muDATA" is the mean vector, "icmDATA" is the inverse covariance matrix, "D" is the dimensionality of the distribution, and "det(cmDATA)" is the determinant of the covariance matrix.

In other words, this equation calculates the probability of observing a particular value of the random vector "v" given the mean and covariance of the distribution, assuming that the variables are normally distributed and independent of each other.