Computer Security Principles and Practice

Business analysis For Practitioners Practice Guide

consensus bridging theory and practice

Distributed source coding is one of the key enablers for efficient cooperative communication. The potential applications range from wireless sensor networks, ad-hoc networks, and surveillance networks, to robust low-complexity video coding, stereo/Multiview video coding, HDTV, hyper-spectral and multispectral imaging, and biometrics. The book is divided into three sections: theory, algorithms, and applications. Part one covers the background of information theory with an emphasis on DSC; part two discusses designs of algorithmic solutions for DSC problems, covering the three most important DSC problems: Slepian-Wolf, Wyner-Ziv, and MT source coding; and part three is dedicated to a variety of potential DSC applications. Key features: Clear explanation of distributed source coding theory and algorithms including both lossless and lossy designs. Rich applications of distributed source coding, which covers multimedia communication and data security applications. Self-contained content for beginners from basic information theory to practical code implementation. The book provides fundamental knowledge for engineers and computer scientists to access the topic of distributed source coding. It is also suitable for senior undergraduate and first year graduate students in electrical engineering; computer engineering; signal processing; image/video processing; and information theory and communications. Table of Contents Chapter 1: Introduction Part I: Theory of Distributed Source Coding Chapter 2: Lossless Compression of Correlated Sources Chapter 3: Wyner–Ziv Coding Theory Chapter 4: Lossy Distributed Source Coding Part II: Implementation Chapter 5: Slepian–Wolf Code Designs Based on Channel Coding Chapter 6: Distributed Arithmetic Coding Chapter 7: Wyner–Ziv Code Design Part III: Applications Chapter 8: Wyner–Ziv Video Coding Chapter 9: Correlation Estimation in DVC Chapter 10: DSC for Solar Image Compression Chapter 11: Secure Distributed Image Coding Chapter 12: Se

差分隐私（英语：differential privacy）是密码学中的一种手段，旨在提供一种当从统计数据库查询时，最大化数据查询的准确性，同时最大限度减少识别其记录的机会。

密码学原理：理论与实践英文版第四版，Cryptography Theory and Practice, 4th Edition，By 作者: Douglas Robert Stinson

卡耐基梅隆大学操作系统教材

英文原版,模型驱动软件建模领域经典书， 作者：Marco Brambilla Politecnico di Milano Jordi Cabot École des Mines de Nantes ManuelWimmer Vienna University of Technology

IEEE Recommended Practice for Software Requirements Specifications1998 IEEE Std 830-1998

ISO26262开发培训--Functional Safety with ISO 26262 - Principles and Practice