Information Theory and Coding provides a very comprehensive analysis of information theory and coding. The fundamental concepts of information theory, namely, source coding, mutual information and channel capacity for discrete and continuous channel are explained using simple mathematical treatment involving probability theory. To make the journey, through the book, an enjoyable experience, a fundamental chapter on probability theory with an inclination towards random variables and random processes is included. Error control coding: The theoretical and practical considerations provided in the book give a concise introduction to basic coding techniques and their utility in practice. The fundamental concepts are explained using a lot of graded examples with minimum use of complex Boolean and statistical tools. The selection of appropriate codes and design of decoders are discussed. The book aims to bridge the gap between digital communications and information theory. This accessible approach will attract students as well as practicing engineers towards the course alike. The clear illustration and explanation will make this book an excellent tool for both communication and electronic engineering students. Features: • Theoretical concepts with necessary mathematical background. • End of chapter problems help in developing the readers and make them understand the most important codes and decoding techniques. • A dedicated chapter on mathematical background that includes probability theory and random processes. • A good coverage of convolution codes and Viterbi algorithm and related implementation issues. • Encoder, decoder and syndrome calculator circuits for cyclic codes have been designed using shift register having feedback connection. • A lot of graded solved examples to strengthen the understanding of theoretical aspects of information and coding theory.