Most data compression methods that are based on variable-length codes employ the Huffman or Golomb codes. However, there are a large number of less-known codes that have useful properties - such as those containing certain bit patterns, or which are robust - and these can be useful. This book brings this large set of codes to the attention of workers in the field and of students of computer science.
David Salomon's crystal clear style of writing and presentation, which has been familiar to readers for many years now allows easy access to the topic. Readers are only required to have a general familiarity with computer methods and essentially an understanding of the representation of data in bits and files.
Computer scientists, electrical engineers and students majoring in computer science or electrical engineering will find this volume an invaluable resource, as will those readers in various physical sciences and mathematics.
David Salomon's crystal clear style of writing and presentation, which has been familiar to readers for many years now allows easy access to the topic. Readers are only required to have a general familiarity with computer methods and essentially an understanding of the representation of data in bits and files.
Computer scientists, electrical engineers and students majoring in computer science or electrical engineering will find this volume an invaluable resource, as will those readers in various physical sciences and mathematics.
"...the greatest contribution of this book is that it brings together and describes such a large number of codes in a succinct manner. ...this book introduces the reader to many lesser-known codes, and conveys an appreciation for the wide variety of codes that exists. ...the author focuses on the principles underlying the codes ...the author includes many diagrams and examples to explain how the algorithms work. In summary, this is a great book for someone new to coding, as well as for someone who just wants to catch up on some of the more contemporary codes."
(W. Hu, ACM Computing Reviews, January 2009)
(W. Hu, ACM Computing Reviews, January 2009)