The Internet of Things (IoT) can enable smart infrastructures to provide advanced services to
the users. New technological advancement can improve our everyday life, even simple tasks …

In this article, a general theoretical framework is developed for the state estimation problem
of stochastic time-varying Boolean networks (STVBNs). The STVBN consists of a system …

Design has become a salient part of most of the scientific and engineering tasks, embracing
a wide range of domains including real experimental settings (eg, material discovery or drug …

In this paper, the particle filtering problem is investigated for a class of stochastic systems
with multiple sensors under signal relays. To improve the performance of signal …

Partially-observed Boolean dynamical systems (POBDS) are a general class of nonlinear
state-space models that provide a rich framework for modeling many complex dynamical …

Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states
to desirable ones has received much attention in recent years. Most of the existing methods …

This paper is concerned with developing particle filters for Boolean networks with multi-step
randomly-delayed measurements. Based on the semi-tensor product of matrices and …

State estimation is important for the synthesis of nonlinear systems with stochastic
disturbances. This work devotes to tackling the optimal state estimation problem of logical …

State-space models (SSMs) are a rich class of dynamical models with a wide range of
applications in economics, healthcare, computational biology, robotics, and more. Proper …

The 21st century is defined as the era of technological development. With drastic increase in
population, automation is becoming the need of the hour in order to make life more …