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.

In molecular biology, the issue of quantifying the similarity between two biological sequences is very important. Past research has shown that word-based search tools are computationally efficient and can find some new functional similarities or dissimilarities invisible to other algorithms like FASTA. Recently, under the independent model of base composition, Wu, Burke, and Davison (1997, Biom...

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...

This paper considers the search problem, introduced by Srivastava cite{Sr}. This is a model discrimination problem. In the context of search linear models, discrimination ability of search designs has been studied by several researchers. Some criteria have been developed to measure this capability, however, they are restricted in a sense of being able to work for searching only one possibl...