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Probability in Electrical Engineering and Computer Science An Application-Driven Course

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This revised textbook motivates and illustrates the techniques of applied probability by applications in electrical engineering and computer science (EECS). The author presents information processing and communication systems that use algorithms based on probabilistic models and techniques, includin...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
1. Verfasser: Walrand, Jean (auth)
Format: Elektronisch Buchkapitel
Sprache:Englisch
Veröffentlicht: Springer Nature 2021
Schlagworte:
Maths for computer scientists
Communications engineering / telecommunications
Maths for engineers
Probability & statistics
Probability and Statistics in Computer Science
Communications Engineering, Networks
Mathematical and Computational Engineering
Probability Theory and Stochastic Processes
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Mathematical and Computational Engineering Applications
Probability Theory
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences
Applied probability
Hypothesis testing
Detection theory
Expectation maximization
Stochastic dynamic programming
Machine learning
Stochastic gradient descent
Deep neural networks
Matrix completion
Linear and polynomial regression
Open Access
Mathematical & statistical software
Stochastics
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