Yury Polyanskiy (Massachusetts Institute of Technology), Yihong Wu (Connecticut Yale University)

Gebundenes Buch

Information Theory

From Coding to Learning

Beschreibung

This enthusiastic introduction to the fundamentals of information theory builds from classical Shannon theory through to modern applications in statistical learning. Includes over 210 student exercises, emphasising practical applications in statistics, machine learning and modern communication theory. Accompanied by online instructor solutions.

Autor

Yury Polyanskiy is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, with a focus on information theory, statistical machine learning, error-correcting codes, wireless communication, and fault tolerance. He is the recipient of the 2020 IEEE Information Theory Society James Massey Award for outstanding achievement in research and teaching in Information Theory.

Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 748
• Erscheinungstermin: 2. Januar 2025
• Englisch
• Abmessung: 260mm x 183mm x 44mm
• Gewicht: 1656g
• ISBN-13: 9781108832908
• ISBN-10: 1108832903
• Artikelnr.: 70725904