There has been great progress in data assimilation within atmospheric and oceanographic
sciences during the last couple of decades. In data assimilation, one aims at merging the …

This book is the outcome of the Indo-French Workshop on ''Matrix Information Geometries
(MIG): Applications in Sensor and Cognitive Systems Engineering,''which was held at École …

Complex multiscale systems are ubiquitous in many areas. This research expository article
discusses the development and applications of a recent information-theoretic framework as …

An accurate estimation of ionospheric variables such as the total electron content (TEC) is
important for many space weather, communication, and satellite geodetic applications …

Any model order reduced dynamical system that evolves a modal decomposition to
approximate the discretized solution of a stochastic PDE can be related to a vector field …

Abstract The Maximum Likelihood Ensemble Filter (MLEF) equations are derived without the
differentiability requirement for the prediction model and for the observation operators. The …

This paper presents a comparative analysis of various nonlinear estimation techniques
when applied for output feedback model-based control of batch crystallization processes …

The multivariate spatio-temporal data contains complex spatio-temporal background and
channel coupling information. Effective extraction of these features is crucial for data …

A sequential estimator based on the Ensemble Kalman Filter for Data Assimilation of fluid
flows is presented in this research work. The main feature of this estimator is that the Kalman …

Accurate forecasting of ocean surface currents is crucial for the planning of marine activities,
including fisheries, shipping, and pollution control. Previous studies have often neglected …