Editor's note: As the following article is a chapter (Chapter 8) from David Koenig's book, Practical Control Engineering: Guide for Engineers, Managers, and Practitioners (MATLAB Examples) (McGraw ...

The field of data science is expanding and changing as new technologies and methods crop up for data scientists. Those familiar with point processes know that they map collections of data points, or ...

We develop a unified stochastic framework for a broad class of nonequilibrium systems and apply it to turbulence and cosmic structure formation. The evolution of spectra and distributions in these ...

Poisson-binomial point processes are gaining considerable momentum, as their applications in the real world are numerous. Point processes map a collection of data points, sometimes called events, that ...

Stochastic processes as a research area focuses on the mathematical modeling and analysis of systems that evolve randomly over time, typically formalized as families of random variables indexed by ...

Stochastic processes are at the center of probability theory, both from a theoretical and an applied viewpoint. Stochastic processes have applications in many disciplines such as physics, computer ...