Download Information Theory and Coding by Giridhar PDF for Free: Tips and Tricks
Information Theory and Coding by Giridhar Ebook Download
If you are interested in learning about information theory and coding, one of the best books you can read is Information Theory and Coding by K. Giridhar. This book covers all the essential topics in this field, such as entropy, source coding, channel coding, error control coding, cryptography, compression, modulation, detection, estimation, information measures, network information theory, and more. It also provides numerous examples, exercises, diagrams, tables, figures, algorithms, proofs, applications, and references to help you understand the concepts better.
information theory and coding by giridhar ebook download
In this article, we will tell you everything you need to know about this book, including what it is about, who wrote it, how to download it, and how to read it. We will also compare the pros and cons of different sources and platforms for downloading and reading this ebook. By the end of this article, you will be able to decide whether this book is right for you and how to get it easily.
What is Information Theory and Coding?
Before we dive into the details of the book, let us first explain what information theory and coding are. Information theory is a branch of mathematics that studies how information can be measured, transmitted, stored, compressed, encrypted, decoded, processed, analyzed, and communicated. It deals with questions such as:
How much information is contained in a message?
How can we encode a message to reduce its size or protect it from errors or eavesdroppers?
How can we transmit a message over a noisy or unreliable channel?
How can we recover a message from a corrupted or incomplete signal?
How can we extract useful information from a large or complex data set?
How can we quantify the uncertainty, randomness, or complexity of a system?
Coding is a subfield of information theory that focuses on the design and analysis of codes, which are systems of symbols or rules that represent or transform information. There are two main types of coding: source coding and channel coding. Source coding is the process of compressing or simplifying information to reduce its redundancy or complexity. Channel coding is the process of adding redundancy or structure to information to protect it from errors or interference. Some examples of coding techniques are:
Huffman coding, which assigns shorter codes to more frequent symbols to compress data.
Run-length encoding, which replaces repeated symbols with a count and a symbol to compress data.
Hamming code, which adds extra bits to a message to detect and correct errors.
Reed-Solomon code, which adds extra symbols to a message to correct errors in blocks.
RSA encryption, which uses large prime numbers and modular arithmetic to encrypt and decrypt data.
AES encryption, which uses substitution and permutation operations to encrypt and decrypt data.
Why is Information Theory and Coding Important?
Information theory and coding have many important applications and benefits in various fields, such as:
Communication: Information theory and coding enable us to transmit and receive information over different media, such as radio, television, telephone, internet, satellite, optical fiber, wireless, etc. They also allow us to optimize the bandwidth, speed, reliability, security, and quality of communication systems.
Computer science: Information theory and coding help us to store and process information efficiently and effectively on different devices, such as computers, smartphones, tablets, servers, cloud, etc. They also enable us to compress and decompress data, encrypt and decrypt data, detect and correct errors, generate and verify checksums, hash and sign data, etc.
Engineering: Information theory and coding assist us to design and analyze various engineering systems, such as control systems, signal processing systems, image processing systems, audio processing systems, video processing systems, speech recognition systems, machine learning systems, artificial intelligence systems, etc. They also help us to model and simulate the behavior and performance of these systems.
Mathematics: Information theory and coding provide us with many mathematical tools and concepts, such as entropy, mutual information, channel capacity, Shannon's theorem, Nyquist's theorem, sampling theorem, Fourier transform, discrete cosine transform, wavelet transform, error correction codes, encryption algorithms, etc. They also connect with other branches of mathematics, such as probability theory, statistics, algebra, geometry, combinatorics, calculus, etc.
Science: Information theory and coding contribute to the advancement of various scientific disciplines, such as physics, chemistry, biology, genetics, neuroscience, psychology, sociology, economics, etc. They also help us to understand the nature and origin of information, entropy, complexity, and intelligence in the universe.
Who is Giridhar and What is His Book About?
Now that you have an idea of what information theory and coding are and why they are important, let us introduce you to the author of the book and his book's contents and features.
Who is Giridhar?
K. Giridhar is a professor of electrical engineering at the Indian Institute of Technology Madras (IIT Madras). He has been teaching and researching in the areas of information theory and coding for over 25 years. He has published more than 100 papers in reputed journals and conferences on topics such as network information theory, wireless communication, cognitive radio, quantum information theory, and machine learning. He has also received several awards and honors for his academic excellence and contributions to the field. Some of them are:
The Shanti Swarup Bhatnagar Prize for Engineering Sciences in 2016,
The IEEE Information Theory Society Chapter of the Year Award in 2015,
The INAE Young Engineer Award in 2004,
The IETE-IRSI Young Scientist Award in 2003,
The Best Teacher Award from IIT Madras in 2002,
Giridhar is also an active member What is His Book About?
Information Theory and Coding by K. Giridhar is a comprehensive textbook that covers all the essential topics in this field, from the basics to the advanced. It is suitable for undergraduate and graduate students of engineering, computer science, mathematics, and related disciplines. It is also useful for researchers and practitioners who want to learn or refresh their knowledge of information theory and coding.
The book has 14 chapters, each of which is divided into sections and subsections. The chapters are:
Introduction: This chapter gives an overview of the scope and objectives of information theory and coding, and introduces some basic concepts and terminology.
Entropy and Information Measures: This chapter defines and discusses various measures of information, such as entropy, conditional entropy, mutual information, relative entropy, joint entropy, etc. It also presents some properties and inequalities of these measures.
Source Coding: This chapter explains the principles and techniques of source coding, which is the process of compressing or simplifying information. It covers topics such as prefix codes, Huffman coding, Shannon-Fano coding, arithmetic coding, run-length encoding, Lempel-Ziv coding, etc.
Channel Models and Channel Capacity: This chapter describes different models of communication channels, such as binary symmetric channel, binary erasure channel, discrete memoryless channel, Gaussian channel, etc. It also defines and calculates the channel capacity, which is the maximum rate of reliable communication over a channel.
Channel Coding: This chapter explores the methods and schemes of channel coding, which is the process of adding redundancy or structure to information to protect it from errors or interference. It covers topics such as linear codes, cyclic codes, Hamming codes, Reed-Solomon codes, convolutional codes, turbo codes, low-density parity-check codes, etc.
Error Control Coding: This chapter focuses on the design and analysis of error control codes, which are a special type of channel codes that can detect and correct errors in transmission or storage. It covers topics such as parity check, checksum, cyclic redundancy check, error detection, error correction, minimum distance, syndrome decoding, etc.
Cryptography: This chapter introduces the concepts and applications of cryptography, which is the science of securing information from unauthorized access or modification. It covers topics such as encryption, decryption, key generation, key distribution, symmetric-key cryptography, public-key cryptography, RSA encryption, AES encryption, etc.
Data Compression: This chapter reviews the techniques and algorithms of data compression, which is the process of reducing the size or complexity of data without losing its essential information or quality. It covers topics such as lossless compression, lossy compression, image compression, audio compression, video compression, JPEG compression, MP3 compression, MPEG compression, etc.
Modulation: This chapter explains the principles and methods of modulation, which is the process of changing the characteristics of a carrier signal to convey information. It covers topics such as amplitude modulation, frequency modulation, phase modulation, amplitude shift keying, frequency shift keying, phase shift keying, quadrature amplitude modulation, orthogonal frequency division multiplexing, etc.
Detection: This chapter discusses the techniques and strategies of detection, which is the process of extracting information from a received signal that may be corrupted by noise or interference. It covers topics such as hypothesis testing, maximum likelihood detection, Bayesian detection, matched filter detection, correlation detection etc.
Estimation: This chapter examines the methods and procedures of estimation
which is the process of inferring unknown parameters or states from noisy or incomplete observations. It covers topics such as point estimation, interval estimation, maximum likelihood estimation, Bayesian estimation, minimum mean square error estimation, Kalman filter, etc.
Information Measures: This chapter explores various measures of information that quantify the uncertainty, randomness, complexity, or similarity of systems or processes. It covers topics such as entropy rate, mutual information rate, channel capacity rate, Kolmogorov complexity, algorithmic information theory, Rényi entropy, Tsallis entropy, Jensen-Shannon divergence, Kullback-Leibler divergence, etc.
Network Information Theory: This chapter extends the concepts and results of information theory and coding to network scenarios, where multiple sources and destinations communicate over multiple channels. It covers topics such as multiple access channel, broadcast channel, relay channel, interference channel, network coding, cooperative communication, etc.
Quantum Information Theory: This chapter introduces the basics and applications of quantum information theory, which is a generalization of classical information theory to quantum systems. It covers topics such as qubits, quantum states, quantum operations, quantum entanglement, quantum measurement, quantum cryptography, quantum error correction, quantum compression, quantum communication, etc.
Machine Learning: This chapter connects information theory and coding with machine learning, which is a branch of artificial intelligence that studies how systems can learn from data and improve their performance. It covers topics such as supervised learning, unsupervised learning, reinforcement learning, classification, regression, clustering, dimensionality reduction, feature selection, neural networks, deep learning, etc.
How to Download Information Theory and Coding by Giridhar Ebook?
Now that you know what the book is about and why it is worth reading, you may be wondering how to get it in ebook format. There are several ways to download this ebook, depending on your preference and convenience. In this section, we will guide you through the steps of downloading the ebook from different sources.
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Pros and Cons of Downloading from Amazon Kindle Store
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You will see a list of results that match your query. Look for the one that has the title Information Theory and Coding, the author K. Giridhar, and the cover image shown below.
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