book

Information Theory, Coding and Cryptography

by Arijit Saha, Nilotpal Manna, Mandal

May 2013

Intermediate to advanced

276 pages

8h 23m

English

Pearson India

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Cover
Title Page
Contents
Foreword
Preface
Part A: Information Theory and Source CodinG
Chapter 1: Probability, Random Processes, and Noise
1.1 Introduction1.2 Fundamentals of Probability1.2.1 Algebra of Probability 1.2.2 Axioms of Probability1.2.3 Elementary Theorems on Probability1.2.4 Conditional Probability1.2.5 Independent Events1.2.6 Total Probability1.3 Random Variables and Its Characteristics1.3.1 Discrete Random Variable and Probability Mass Function 1.3.2 Cumulative Distribution Function1.3.3 Distribution Function for Discrete Random Variable1.3.4 Continuous Random Variable and Probability Density Function1.4 Statistical Averages 1.5 Frequently Used Probability Distributions 1.5.1 Binomial Distribution 1.5.2 Poisson Distribution 1.5.3 Gaussian Distribution 1.6 Random Processes 1.7 Noise 1.7.1 Sources of Noise 1.7.2 Thermal Noise 1.7.3 Shot Noise 1.7.4 Partition Noise 1.7.5 Flicker Noise or 1/f Noise 1.8 Solved Problems Multiple Choice Questions Review Questions
Chapter 2: Information Theory
2.1 Introduction 2.2 Measure of Information 2.3 Entropy 2.4 Information Rate 2.5 Channel Model 2.5.1 Discrete Memoryless Channel 2.5.2 Special Channels 2.6 Joint Entropy and Conditional Entropy 2.7 Mutual Information 2.8 Channel Capacity 2.8.1 Special Channels 2.9 Shannon’s Theorem 2.10 Continuous Channel 2.10.1 Differential Entropy 2.10.2 Additive White Gaussian Noise Channel 2.10.3 Shannon–Hartley Law 2.11 Solved ProblemsMultiple Choice Questions Review Questions
Chapter 3: Source Codes
3.1 Introduction 3.2 Coding Parameters 3.3 Source Coding Theorem 3.4 Classification of Codes 3.5 Kraft Inequality 3.6 Image Compression 3.6.1 Image Formats, Containers, and Compression Standards 3.7 Speech and Audio Coding 3.8 Shannon–Fano Coding 3.9 Huffman Coding 3.10 Arithmetic Coding 3.11 Lempel–Ziv–Welch Coding 3.12 Run-length Encoding 3.13 MPEG Audio and Video Coding Standards 3.14 Psychoacoustic Model of Human Hearing 3.14.1 The Masking Phenomenon 3.14.2 Temporal Masking 3.14.3 Perceptual Coding in MPEG Audio 3.15 Dolby 3.16 Linear Predictive Coding Model 3.17 Solved Problems Multiple Choice Questions Review Questions
Part B: Error Control Coding

Chapter 4: Coding Theory
4.1 Introduction4.2 Types of Codes 4.2.1 Code Rate4.3 Types of Errors 4.4 Error Control Strategies 4.4.1 Throughput Efficiency of ARQ 4.5 Mathematical Fundamentals4.5.1 Modular Arithmetic 4.5.2 Sets 4.5.3 Groups 4.5.4 Fields 4.5.5 Arithmetic of Binary Field 4.5.6 Roots of Equations 4.5.7 Galois Field 4.6 Vector Spaces 4.6.1 Subspace 4.6.2 Linear Combination 4.6.3 Basis (or Base) 4.6.4 Dimension 4.6.5 Orthogonality 4.6.6 Dual Space 4.7 Matrices 4.7.1 Row Space 4.8 Solved Problems Multiple Choice Questions Review Questions
Chapter 5: Linear Block Codes
5.1 Introduction 5.2 Generator Matrices 5.3 Parity-check Matrices 5.3.1 Dual Code 5.4 Error Syndrome 5.4.1 Undetectable Error Pattern 5.5 Error Detection 5.6 Minimum Distance 5.7 Error-detecting Capability 5.8 Error-correcting Capability5.9 Standard Array and Syndrome Decoding 5.9.1 Coset and Coset Leader 5.10 Probability of Undetected Errors Over a BSC 5.11 Hamming Code 5.12 Solved Problems Multiple Choice Questions Review Questions
Chapter 6: Cyclic Codes
6.1 Introduction 6.2 Generation 6.2.1 Generation and Parity-check Matrices 6.2.2 Realization of Cyclic Code 6.3 Syndrome Computation and Error Detection 6.4 Decoding6.5 Cyclic Hamming Code 6.6 Shortened Cyclic Code 6.7 Golay Code 6.8 Error-trapping Decoding 6.8.1 Improved Error-trapping 6.9 Majority Logic Decoding 6.10 Cyclic Redundancy Check 6.11 Solved Problems Multiple Choice Questions Review Questions
Chapter 7: BCH Codes
7.1 Introduction 7.2 Primitive Elements 7.3 Minimal Polynomials 7.4 Generator Polynomials 7.5 Decoding of BCH Codes 7.6 Implementation of Galois Field7.7 Implementation of Error Correction 7.7.1 Syndrome Computation 7.7.2 Computation of Error Location Polynomial 7.8 Nonbinary BCH Codes 7.8.1 Reed–Solomon Code 7.9 Weight Distribution 7.10 Solved Problems Multiple Choice Questions Review Questions
Chapter 8: Convolution Codes
8.1 Introduction 8.2 Tree and Trellis Codes 8.3 Encoding 8.4 Properties 8.4.1 Structural Properties 8.4.2 Distance Properties 8.5 Decoding 8.5.1 Threshold Decoding 8.5.2 Sequential Decoding 8.5.3 Viterbi Decoding 8.6 Construction 8.7 Implementation and Modification 8.8 Applications 8.9 Turbo Coding and Decoding 8.10 Interleaving Techniques: Block and Convolution 8.11 Coding and Interleaving Applied to CD Digital Audio System 8.11.1 CIRC Encoding and Decoding 8.11.2 Interpolation and Muting 8.12 Solved Problems Multiple Choice Questions Review Questions
Part C: Cryptography
Chapter 9: Cryptography
9.1 Introduction 9.2 Plain Text, Cipher Text, and Key 9.3 Substitution and Transposition 9.4 Encryption and Decryption 9.5 Symmetric-key Cryptography 9.5.1 Stream Ciphers and Block Ciphers 9.6 Data Encryption Standard 9.6.1 Basic Principle 9.6.2 Initial Permutation 9.6.3 Details of Single Round 9.6.4 Inverse Initial Permutation 9.6.5 DES Decryption 9.6.6 Strength of DES 9.7 Advance Versions of DES 9.7.1 Double DES 9.7.2 Triple DES 9.8 Asymmetric-key Cryptography 9.8.1 Public and Private Key 9.9 RSA Algorithm 9.9.1 Example of RSA 9.9.2 Strength of RSA 9.10 Symmetric versus Asymmetric-key Cryptography 9.11 Diffie–Hellman Key Exchange 9.11.1 The Algorithm 9.12 Steganography 9.13 Quantum Cryptography 9.14 Solved Problems Multiple Choice Questions Review Questions
Appendix A: Some Related Mathematics
A.1 Fermat’s Little Theorem A.2 Chinese Remainder Theorem A.3 Prime Number Generation A.3.1 Sieve of Eratosthenes
Notes
Bibliography
Copyright
Back Cover

Overview

Information Theory, Coding & Cryptography has been designed as a comprehensive text for the students of engineering discussing Source Encoding, Error Control Codes & Cryptography. The book contains the recent developments of coded modulation, trellises for codes, turbo coding for reliable data and interleaving. The text balances the mathematical rigor with exhaustive amount of solved, unsolved questions along with a database of MCQ's.

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