As more applications are found, interest in Hidden Markov Models continues to grow.
Following comments and feedback from colleagues, students and other working with Hidden …

This paper gives a precise meaning to the robustness of risk-sensitive filters for problems in
which one is uncertain as to the exact value of the probability model. It is shown that risk …

We propose a new risk-constrained reformulation of the standard Linear Quadratic
Regulator (LQR) problem. Our framework is motivated by the fact that the classical (risk …

An event-triggered risk-sensitive state estimation problem for hidden Markov models is
investigated in this work. The event-triggered scheme considered is fairly general, which …

During the seven years that elapsed between the first and second editions of the present
book, considerable progress was achieved in the area of financial modelling and pricing of …

This paper proposes a novel state estimation strategy with globalized robustness for a class
of systems under uncertainty. Departing from the classical minimax estimation, this paper …

In this paper, we consider an event-triggered minimax state estimation problem for uncertain
systems subject to a relative entropy constraint. This minimax estimation problem is …

We propose a new risk-constrained formulation of the classical Linear Quadratic (LQ)
stochastic control problem for general partially-observed systems. Our framework is …

This paper studies a quantum risk-sensitive estimation problem and investigates robustness
properties of the filter. This is a direct extension to the quantum case of analogous classical …

In this work, we investigate a robust event-triggered remote state estimation problem for
linear Gaussian systems with a stochastic event-triggering condition. The reference measure …