|
Showing 1 - 2 of
2 matches in All Departments
Through information theory, problems of communication and
compression can be precisely modeled, formulated, and analyzed, and
this information can be transformed by means of algorithms. Also,
learning can be viewed as compression with side information. Aimed
at students and researchers, this book addresses data compression
and redundancy within existing methods and central topics in
theoretical data compression, demonstrating how to use tools from
analytic combinatorics to discover and analyze precise behavior of
source codes. It shows that to present better learnable or
extractable information in its shortest description, one must
understand what the information is, and then algorithmically
extract it in its most compact form via an efficient compression
algorithm. Part I covers fixed-to-variable codes such as Shannon
and Huffman codes, variable-to-fixed codes such as Tunstall and
Khodak codes, and variable-to-variable Khodak codes for known
sources. Part II discusses universal source coding for memoryless,
Markov, and renewal sources.
The term analytic information theory has been coined to describe
problems of information theory studied by analytic tools. The
approach of applying tools from analysis of algorithms to problems
of source coding and, in general, to information theory lies at the
crossroad of computer science and information theory. Combining the
tools from both areas often provides powerful results, such as
computer scientist Abraham Lempel and information theorist Jacob
Ziv working together in the late 1970s to develop compression
algorithms that are now widely referred to as Lempel-Ziv algorithms
and are the basis of the ZIP compression still used extensively in
computing today. This monograph surveys the use of these techniques
for the rigorous analysis of code redundancy for known sources in
lossless data compression. A separate chapter is devoted to precise
analyses of each of three types of lossless data compression
schemes, namely fixed-to-variable length codes, variable-to-fixed
length codes, and variable-to-variable length codes. Each one of
these schemes is described in detail, building upon work done in
the latter part of the 20th century to present new and powerful
techniques. For the first time, this survey presents redundancy for
universal variable-to-fixed and variable-to-variable length codes
in a comprehensive and coherent manner. The monograph will be of
interest to computer scientists and information theorists working
on modern coding techniques. Written by two leading experts, it
provides the reader with a unique, succinct starting point for
their own research into the area.
|
|