## Basic Concepts in Information Theory and Coding: The Adventures of Secret Agent 00111Basic Concepts in Information Theory and Coding is an outgrowth of a one semester introductory course that has been taught at the University of Southern California since the mid-1960s. Lecture notes from that course have evolved in response to student reaction, new technological and theoretical develop ments, and the insights of faculty members who have taught the course (in cluding the three of us). In presenting this material, we have made it accessible to a broad audience by limiting prerequisites to basic calculus and the ele mentary concepts of discrete probability theory. To keep the material suitable for a one-semester course, we have limited its scope to discrete information theory and a general discussion of coding theory without detailed treatment of algorithms for encoding and decoding for various specific code classes. Readers will find that this book offers an unusually thorough treatment of noiseless self-synchronizing codes, as well as the advantage of problem sections that have been honed by reactions and interactions of several gen erations of bright students, while Agent 00111 provides a context for the discussion of abstract concepts. |

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Basic Concepts in Information Theory and Coding Solomon W. Golomb,Robert E. Peile,Robert A. Scholtz No preview available - 2014 |

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Agent alphabet ambiguously decodable assume asymptotic average binary code binary symmetric channel bits block code channel matrix Chernoff bound code word comma-free code compute Consider construction contains convex convolutional codes cyclic equivalence class decoding algorithm defined denotes determine diagram dictionary elements encoding equal ergodic error rate Error-Correcting Codes Euclidean distance Example exists finite given Hamming distance Hence IEEE Trans indicates inequality infinite Information Theory integer interleaving lattice Lempel-Ziv mapping Markov source maximum memoryless channel minimum distance modulation mutual information n-tuple noiseless channel Note NPCE classes packet perfect codes possible prefix probability distribution probability vector problem random variables reliable communication result Section Seg table selected sequence of code shown in Figure side of Equation source message squared Euclidean distance stationary suffix Synchronizable Codes synchronization transition probabilities transmission transmitted tuples uncertainty uniquely decodable upper bound word length words of length zero