Learn the fundamentals of information theory, including entropy, coding, and data compression, while exploring advanced topics like transfer entropy, thermodynamics, and real-world applications.Key FeaturesA clear blend of foundational theory and advanced topics suitable for various expertise levels

Learn the fundamentals of information theory, including entropy, coding, and data compression, while exploring advanced topics like transfer entropy, thermodynamics, and real-world applications.

Key Features

• A clear blend of foundational theory and advanced topics suitable for various expertise levels
• A focus on practical examples to complement theoretical concepts and enhance comprehension
• Comprehensive coverage of applications, including data compression, thermodynamics, and biology

Book Description

This book offers a comprehensive journey through the fascinating world of information theory, beginning with the fundamental question: what is information? Early chapters introduce key concepts like entropy, binary representation, and data compression, providing a clear and accessible foundation. Readers explore Shannon's source coding theorem and practical tools like Huffman coding to understand how information is quantified and optimized. Building on these basics, the book delves into advanced topics such as the noisy channel coding theorem, mutual information, and error correction techniques. It examines entropy in continuous systems, channel capacity, and rate-distortion theory, making complex ideas accessible through real-world examples. Connections between information and thermodynamics are also explored, including Maxwell’s Demon, the Landauer Limit, and the second law of thermodynamics. The final chapters tie information theory to biology and artificial intelligence, investigating its role in evolution, the human genome, and brain computation. With practical examples throughout, this book balances theoretical depth with hands-on learning, making it an essential resource for mastering information theory. A basic mathematical foundation will be beneficial but is not required to engage with the material.

What you will learn

• Understand the core concepts of information theory
• Analyze entropy in discrete and continuous systems
• Explore Shannon's source and channel coding theorems
• Apply Huffman coding and data compression techniques
• Examine mutual information and its significance
• Relate thermodynamic entropy to information theory

Who this book is for

This book is perfect for students, engineers, and researchers in computer science, electrical engineering, physics, and related fields. A basic mathematical foundation will enhance understanding and ensure readers can fully grasp the concepts and their practical applications.