Estimating the square root of probability density function on Riemannian manifold
Estimating the square root of probability density function on Riemannian manifold
Abstract We propose that the square root of a probability density function can be represented as a linear combination of Gaussian kernels. It is shown that if the Gaussian kernel centres and kernel width are known, then the maximum likelihood parameter estimator can be formulated as a Riemannian optimisation problem …