Nonnegative matrix factorization (NMF) is a standard linear dimensionality reduction technique for nonnegative data sets. In order to measure the discrepancy between input and low-rank approximation, Kullback-Leibler (KL) divergence one of most widely used objective function NMF. It corresponds maximum likehood estimator when underlying statistics observed sample follows Poisson distribution, K...

We define a new measure of causation from fluctuation-response theorem for Kullback-Leibler divergences, based on the information-theoretic cost perturbations. This information response has both invariance properties required an and physical interpretation propagation In linear systems, reduces to transfer entropy, providing connection between Fisher mutual information.

Abstract Adopting a joint approach toward state estimation and integrity monitoring results in unbiased unlike traditional approaches. So far, was used particle RAIM (Gupta & Gao, 2019) for GNSS measurements only. In our work, we extend Particle to GNSS-camera fused system monitoring. To account vision faults, derived probability distribution over position from camera images using ...

Partial Discharge (PD) is the most important source of insulation degradation in power transformers. In order to prevent catastrophic failures in transformers, PDs need to be located as soon as possible so that maintenance measures can be taken in time. Due to the structural complexity of windings, locating the PD source inside a transformer winding is not a simple task. In this paper, the effi...

In this paper, we present a method for reducing a regular, discrete-time Markov chain (DTMC) to another DTMC with a given, typically much smaller number of states. The cost of reduction is defined as the Kullback–Leibler divergence rate between a projection of the original process through a partition function and a DTMC on the correspondingly partitioned state space. Finding the reduced model w...