Jan 1, 2002 · Pillai teaches Probability theory, Stochastic Processes, Detection and Estimation theory, Principles of Communication Theory, all catered to Electrical Engineering applications.

Let Z(t) = X(t)+Y(t), where X(t) and Y(t) are jointly stationary random processes. Also assume that X(t) and Y(t) are uncorrelated and at least one of them has zero mean.

This book, updated significantly from the previous edition, is intended for a senior/graduate level course in probability and is aimed at students in electrical engineering, maths and physics …

The first three chapters develop probability theory and introduce the axioms of probability, random variables, and joint distributions. The following two chapters are shorter and of an …

May 8, 2012 · Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present …

The fourth edition of "Probability, Random Variables, and Stochastic Processes" has been significantly updated to enhance its educational value for engineers and physicists.

These notes grew from an introduction to probability theory taught during the first and second term of 1994 at Caltech.

In probability theory and related fields, a stochastic (/ stəˈkæstɪk /) or random process is a mathematical object usually defined as a family of random variables in a probability space, …

In contrast to the case of random vectors or random variables, it is not easy to define a notion of a density (or a probability mass function) for a stochastic process.

Probability and Stochastic Processes after Erhan Cinlar and Sheldon M. Ross, notes by Billy Fang