![](/common/images/spacer.gif)
![Wolfram Library Archive](/images/database/subheader.gif)
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) Modeling Random Systems
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif)
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif)
Publisher: | Pearson Education, Inc. (New Jersey) |
| ![](/common/images/spacer.gif) | ![Book cover image](https://media.wolfram.com/books/ISBN0131414372.jpg) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) The Probability Paradigm | The Binomial Model and Random Variables | Continuous Random Variables and the Gaussian Model | Statistics | The Poisson Model | Modeling Random Signals | Tutorial on Mathematica | Tutorial on Convolution | Summary of Common Probability Models | Index
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) An introductory textbook for undergraduate engineering students learning the basic concepts of randomness and modeling random systems. Features include easy-to-follow lessons, end-of-chapter problems, and a quick tutorial on using Mathematica for real-life modeling situations. The publisher will distribute an electronic version.
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif)
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/images/database/grey-line.gif) |
![](/images/database/grey-line.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) Signal Processing, Binomial model, Coherence Function, Ergotic, Random Variables, Noise, Wide Sense Stationary
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
|
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
![](/common/images/spacer.gif) |
| | | | ![](/common/images/spacer.gif) | |
|