This book concerns the identification of systems in which only quantized output observations
are available, due to sensor limitations, signal quantization, or coding for communications …

This book describes the classical smoothing, filtering and prediction techniques together
with some more recently developed embellishments for improving performance within …

The traditional paradigm of system identification employs prior information on system
structures and environments and input/output observation data to derive system models …

This brief presents a novel adaptive iterative learning control (ILC) algorithm for a class of
single parameter systems with binary-valued observations. Using the certainty equivalence …

Dynamical systems with binary-valued observations are widely used in information industry,
technology of biological pharmacy and other fields. Though there have been much efforts …

This paper is concerned with the optimal identification problem of dynamical systems in
which only quantized output observations are available under the assumption of fixed …

This work is concerned with identification of Wiener systems whose outputs are measured
by binary-valued sensors. The system consists of a linear FIR (finite impulse response) …

This paper addresses the identification of finite impulse response (FIR) systems with both
quantized and event-triggered observations. An event-triggered communication scheme for …

State observability and observer designs are investigated for linear-time-invariant systems in
continuous time when the outputs are measured only at a set of irregular sampling time …

This paper investigates a multi-agent asymptotic consensus problem with binary-valued
observations and observation uncertainty. This uncertainty is described by an additive …