Fighting Earth's degradation and safeguarding the environment are subjects of topical
interest and sources of hot debate in today's society. According to the United Nations, there …

Zeroth-order (ZO) optimization is a subset of gradient-free optimization that emerges in many
signal processing and machine learning (ML) applications. It is used for solving optimization …

Data-driven discovery is revolutionizing how we model, predict, and control complex
systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and …

Data science, and machine learning in particular, is rapidly transforming the scientific and
industrial landscapes. The aerospace industry is poised to capitalize on big data and …

Optimal sensor and actuator placement is an important unsolved problem in control theory.
Nearly every downstream control decision is affected by these sensor and actuator …

We study the problem of selecting the best sampling set for bandlimited reconstruction of
signals on graphs. A frequency domain representation for graph signals can be defined …

In millimeter-wave communications, multiple-input-multiple-output (MIMO) systems use large
antenna arrays to achieve high gain and spectral efficiency. These massive MIMO systems …

The problem of estimating underlying trends in time series data arises in a variety of
disciplines. In this paper we propose a variation on Hodrick–Prescott (HP) filtering, a widely …

The reliability of driving perception systems under unprecedented conditions is crucial for
practical usage. Latest advancements have prompted increasing interest in multi-LiDAR …

The problem of choosing the best subset of sensors that guarantees a certain estimation
performance is referred to as sensor selection. In this paper, we focus on observations that …