The field of identification and process-parameter estimation has developed rapidly during
the past decade. In this survey paper the state-of-the-art/science is presented in a systematic …

Real-time control systems rely on reliable estimates of states and parameters in order to
provide accurate and safe control of electro-mechanical systems. The task of extracting state …

The book systematically introduces theories of frequently-used modern signal processing
methods and technologies, and focuses discussions on stochastic signal, parameter …

This book may be regarded as consisting of two parts. In Chapters I-IV we pre sent what we
regard as essential topics in an introduction to deterministic optimal control theory. This …

To implement fault-tolerant quantum computation with continuous variables, the Gottesman-
Kitaev-Preskill (GKP) qubit has been recognized as an important technological element …

The classical filtering and prediction problem is re-examined using the Bode-Shannon
representation of random processes and the “state-transition” method of analysis of dynamic …

At the end of 1960s and the beginning of 1970s, when the Russian version of this book was
written, the'general theory of random processes' did not operate widely with such notions as …

The definitive textbook and professional reference on Kalman Filtering–fully updated,
revised, and expanded This book contains the latest developments in the implementation …

Atmospheric Data Analysis is intended to fill a void in the atmospheric science literature and
curricula. The book is self contained, and includes topics important in several other fields …

This paper presents a method for modeling and estimation of the state of charge (SOC) of
lithium-ion (Li-Ion) batteries using neural networks (NNs) and the extended Kalman filter …