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Intuitive Probability and Random Processes using MATLAB®

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

16.11.2005

Verlag

Springer Us

Seitenzahl

834

Maße (L/B/H)

26/18,3/5 cm

Gewicht

1775 g

Auflage

1. st ed. 2006

Sprache

Englisch

ISBN

978-0-387-24157-9

Beschreibung

Rezension

From the reviews:"The book is composed of 22 chapters. … This is a very readable book. … Kay’s book undoubtedly will see its greatest use in engineering schools, but I think it would work nicely in other settings as well. … It is written in a clear and informal style that students will appreciate, its coverage is excellent, and the author’s stated objective (to lessen the difficulty that students usually experience assimilating and applying probability and random processes) will, I predict, be met." (Ralph P. Russo, The American Statistician, Vol. 62 (2), May, 2008)“Kay’s book occupies a unique place in the overcrowded market of textbooks on probability and random processes. … This new textbook is a breath of fresh air in the market of books devoted to probability and random processes. The book lives up to its ambition of setting a new standard for a modern, computer-based treatment of the subject. … I fully recommend its use in undergraduate and first-year graduate courses.” (Osvaldo Simeone, IEEE Control Systems Magazine, Vol. 27, June, 2007)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

16.11.2005

Verlag

Springer Us

Seitenzahl

834

Maße (L/B/H)

26/18,3/5 cm

Gewicht

1775 g

Auflage

1. st ed. 2006

Sprache

Englisch

ISBN

978-0-387-24157-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Intuitive Probability and Random Processes using MATLAB®
  • Produktbild: Intuitive Probability and Random Processes using MATLAB®
  • 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.