Using a simple yet rigorous approach‎,‎ Algebraic and Stochastic Coding Theory makes the subject of coding theory easy to understand for readers with a thorough knowledge of digital arithmetic‎,‎ Boolean and modern algebra‎,‎ and probability theory‎.‎ It explains the underlying principles of coding theory and offers a clear‎,‎ detailed description of each code‎.‎ More advanced readers will appreciate its coverage of recent developments in coding theory and stochastic processes‎.‎ After a brief review of coding history and Boolean algebra‎,‎ the book introduces linear codes‎,‎ including Hamming and Golay codes‎.‎ It then examines codes based on the Galois field theory as well as their application in BCH and especially the Reed‎-Solomon codes that have been used for error correction of data transmissions in space missions‎.‎ The major outlook in coding theory seems to be geared toward stochastic processes‎,‎ and this book takes a bold step in this direction‎.‎ As research focuses on error correction and recovery of erasures‎,‎ the book discusses belief propagation and distributions‎.‎ It examines the low‎-density parity‎-check and erasure codes that have opened up new approaches to improve wide‎-area network data transmission‎.‎ It also describes modern codes‎,‎ such as the Luby transform and Raptor codes‎,‎ that are enabling new directions in high‎-speed transmission of very large data to multiple users‎.‎ This robust‎,‎ self‎-contained text fully explains coding problems‎,‎ illustrating them with more than 200 examples‎.‎ Combining theory and computational techniques‎,‎ it will appeal not only to students but also to industry professionals‎,‎ researchers‎,‎ and academics in areas such as coding theory and signal and image processing‎.‎