Information Theory Step-by-Step: Concepts, Applications, and Problem-Solving in Data, Signals & Communication
Information Theory Step-by-Step: Concepts, Applications, and Problem-Solving in Data, Signals & Communication (Step By Step Subject Guides) by Julian Nash
English | May 25, 2024 | ISBN: N/A | ASIN: B0D57XG5QC | PDF | 2.29 Mb
English | May 25, 2024 | ISBN: N/A | ASIN: B0D57XG5QC | PDF | 2.29 Mb
Are you curious about the principles that make modern communication and data processing possible? "Information Theory Step-by-Step" is your ultimate resource. This book guides you through information theory and its core concepts, practical applications, and advanced problem-solving techniques.
Key Features:
- Comprehensive Coverage: Learn the history, evolution, and fundamental principles of information theory. Understand the mathematical foundations and key contributors.
- Clear and Accessible: Written in a clear, friendly style, this book breaks down complex mathematical concepts into easy-to-understand explanations. Each chapter builds logically from basic to advanced topics, ensuring you develop a solid understanding before moving on.
- Real-World Applications: Discover how information theory is applied in everyday technology, from data compression techniques in multimedia streaming to error-correcting codes in wireless networks. Learn about its role in communication systems, cryptography, and even biology.
- Practical Problem-Solving: Find practical tools and techniques to solve real-world problems. This book includes numerous examples and case studies to reinforce your understanding and help apply information theory concepts in various scenarios.
- Advanced Topics: Explore advanced topics like rate-distortion theory, network information theory, and quantum information theory. Gain insights into the latest research and emerging trends.
- Easy-to-Follow Chapters: Chapters on probability theory, entropy, source coding, channel capacity, data compression, coding theory, communication systems, machine learning applications, quantum information, and more.
Whether you're a student, researcher, or professional in computer science, electrical engineering, data science, or a related field, "Information Theory Step-by-Step" is the perfect companion. It provides a comprehensive introduction for beginners while offering insights for advanced learners seeking to expand their knowledge.
What You'll Learn:
- Introduction to Information Theory: Explore the history, key contributors, and milestones. Understand fundamental concepts, definitions, and mathematical foundations.
- Probability Theory Basics: Master probability distributions, random variables, expectation, variance, and essential theorems like the law of large numbers and central limit theorem.
- Entropy and Information: Learn about entropy, its properties, and its relationship with information content. Study joint, conditional, and relative entropy, and mutual information.
- Source Coding and Channel Capacity: Go into Shannon's source coding theorem, Huffman coding, arithmetic coding, and various channel capacities.
- Data Compression Techniques: Understand lossless and lossy compression methods, including run-length encoding and the Lempel-Ziv-Welch algorithm.
- Coding Theory: Explore error-correcting codes like Hamming, BCH, convolutional, turbo, and LDPC codes.
- Communication Systems: Discover the role of information theory in digital modulation, performance measures, and modern communication systems like Wi-Fi and cellular networks.
- Advanced Topics: Investigate rate-distortion theory, multi-user information theory, and information-theoretic security.
- Applications in Data Science and Machine Learning: See how information theory aids in feature selection, decision trees, and machine learning algorithms.
- Quantum Information Theory: Get introduced to quantum mechanics basics, quantum entropy, and quantum error correction.