Intuitive Probability and Random Processes using MATLAB is an introduction toprobability 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 descriptionsof "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have tostudy this?" Other salient features are:.*heavy reliance on computer simulation for illustration and student exercises .*the incorporation of MATLAB programs and code segments .*discussion of discrete random variables followed by continuous random variables to minimize confusion .*summary sections at the beginning of each chapter .*in-line equation explanations .*warnings on common errors and pitfalls .*over 750 problems designed to help the reader assimilate andextend the concepts .Intuitive Probability and Random Processes using MATLAB is intended for undergraduate and first-year graduate students in engineering.The practicing engineer as well as others having the appropriate mathematicalbackground will also benefit from this book. About the Author.Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts." from the IEEE Signal Processing society and has been listed as among the250 most cited researchers in the world in engineering. INDICE: Introduction.- 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 ContinuousRandom 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.- Appendix A: Glossary of Symbols and Abbreviations.- Appendix B: Assorted Math Facts and Formulas.- Appendix C: Linear and Matrix Algebra.- Appendix D: Summary of Signals, Linear Transforms, and Linear Systems.- Appendix E: Answers to Selected Problems.
- ISBN: 978-0-387-24157-9
- Editorial: Springer
- Encuadernacion: Cartoné
- Páginas: 650
- Fecha Publicación: 05/03/2012
- Nº Volúmenes: 1
- Idioma: Inglés