Stochastic Processes

This piece introduces stochastic processes as probabilistic models of data streams. It illustrates the breadth of such streams with examples ranging from speech, audio, and video signals to stock market prices and measurements of physical phenomena recorded by digital sensors such as medical instruments, GPS receivers, and seismographs.

The central point is that a solid understanding of the mathematical basis of these models is essential both for understanding phenomena and for processing information. The author notes this foundation is important across many branches of science and engineering, including physics, communications, signal processing, automation, and structural dynamics, underscoring the wide applicability of the theory.