Network systems consist of subsystems and their interconnections and provide a powerful
framework for the analysis, modeling, and control of complex systems. However, subsystems …

Probabilistic finite state automata (PFSA) are often constructed from symbol strings that, in
turn, are generated by partitioning time series of sensor signals. This paper focuses on a …

This paper proposes a long-range (LoRa)-based outdoor localization and tracking method.
Our method presents an unsupervised localization approach that utilizes symbolized LoRa …

The PageRank algorithm employed at Google assigns a measure of importance to each
web page for rankings in search results. In our recent papers, we have proposed a …

Wireless communication networks can be well-modeled by Markov Decision Processes
(MDPs). While traditional dynamic programming algorithms such as value and policy …

This paper presents an approach for the interactive visualization, exploration and
interpretation of large multivariate time series. Interesting patterns in such datasets usually …

Modeling unknown systems from data is a precursor of system optimization and sequential
decision making. In this paper, we focus on learning a Markov model from a single trajectory …

This paper proposes an aggregation-based model reduction method for nonlinear models of
multi-zone building thermal dynamics. The full-order model, which is already a lumped …

Complex systems, abstractly represented as networks, are ubiquitous in everyday life.
Analyzing and understanding these systems requires, among others, tools for community …

To achieve the goal of drawing up optimal plans for power generation, decision makers
need an appropriate methodology to effectively identify the pivotal aspects of electricity …