Computer Simulation -- Basic Probability -- Conditional Probability -- Discrete Random Variables -- Expected Values for Discrete Random Variables -- Multiple Discrete Random Variables -- Conditional Probability Mass Functions -- Discrete N-Dimensional Random Variables -- Continuous Random Variables -- Expected Values for Continuous Random Variables -- Multiple Continuous Random Variables -- Conditional Probability Density Functions -- Continuous N-Dimensional Random Variables -- Probability and Moment Approximations Using Limit Theorems -- Basic Random Processes -- Wide Sense Stationary Random Processes -- Linear Systems and Wide Sense Stationary Random Processes -- Multiple Wide Sense Stationary Random Processes -- Gaussian Random Processes -- Poisson Random Processes -- Markov Chains
Summary
"This book is an introduction to probability and random processes that merges theory with practice. Based on the author's belief that only "hands on" experience with the material can promote intuitive understanding the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications."--Jacket
