This book...

• Features contributions from an international array of established and emerging scholars from across the humanities
• Explores the historical development of...

This text unifies the concepts of information, codes and cryptography as first studied by Shannon in his seminal papers on communication and secrecy systems. The first five chapters cover the fundamental ideas of information theory, compact encoding of messages and the theory of error-correcting codes. After a discussion of mathematical...

• Fully-coded working examples using a wide range of machine learning libraries and tools, including Python, R, Julia, and Spark
• Comprehensive practical solutions taking you into the future of machine learning
• Go a step further and integrate your machine learning projects with...

While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic...

This book is an elementary self-contained introduction to some constructions of representation theory and related topics of differential geometry and analysis. Topics covered include the theory of various Fourier-like integral operators such as Segal-Bargmann transforms, Gaussian integral operators in $L^2$ and in the Fock space, integral...

Pseudo-random sequences are essential ingredients of every modern digital communication system including cellular telephones, GPS, secure internet transactions and satellite imagery. Each application requires pseudo-random sequences with specific statistical properties. This book describes the design, mathematical analysis and implementation...

A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible...