K-distribution

About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.

Markov random walk representations with continuous distributions

Abstract: Representations based on random walks can exploit discrete data distributions for clustering and classification. We extend such representations from discrete to continuous distributions. Transition probabilities are now calculated using a diffusion equation with a diffusion coefficient that inversely depends on the data density. We relate this diffusion equation to a path integral and derive the corresponding path probability measure. The framework is useful for incorporating continuous data densities and prior knowledge.

Intrinsic probability distributions for physical systems

Abstract: For a given metric $g_{\mu u}$, which is identified as Fisher information metric, we generate new constraints for the probability distributions for physical systems. We postulate the existence of intrinsic probability distributions for physical systems, and calculate the probability distribution by optimizing the Fisher information metric under specified constraints. Accordingly, we get differential equations for the probability distributions.