Probability Distributions Involving Gaussian Random Variables

Produktinformationen "Probability Distributions Involving Gaussian Random Variables"
This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume. This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. The book has been endorsed by top experts in the field worldwide, ensuring quality and value. It offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling. Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume. Concise compilation of disparate formulae saves time in searching different sources. The material in this book is timeless and has intrinsic value to today’s and tomorrow’s practicing engineers and scientists.
Autor: Simon, Marvin K.
ISBN: 9781402070587
Verlag: Springer US
Auflage: 1
Sprache: Englisch
Seitenzahl: 200
Produktart: Gebunden
Erscheinungsdatum: 31.05.2002
Verlag: Springer US
Untertitel: A Handbook for Engineers and Scientists
Schlagworte: MATLAB Mathematica Probability distribution RSI Random variable Signal communication electrical engineering image processing modeling

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Probability Distributions Involving Gaussian Random Variables
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