Applications
- 181
- Edel, Yves
- University of Heidelberg. Includes examples of linear codes, constant-weight codes and quantum codes.
- 182
- Gupta, Manish K
- Research interests include information processing in Biology, bio-molecular computing, coding and information theory, cryptology, quantum computing, computational, structural and systems biology and bioinformatics. CV and publications.
- 183
- Wood, Jay
- Western Michigan University. Algebraic coding theory, especially mathematical structure of linear codes over finite rings.
- 185
- The Art of Error Correcting Coding
- Web site of the book "The Art of Error Correcting Coding" by R. Morelos-Zaragoza, Wiley, 2002. Source code in C language for numerous error correcting schemes.
- 186
- (Germany) Christian-Albrechts-Universität, Kiel
- Information and coding theory laboratory. Staff, teaching, publications.
- 187
- Laboratory of Natural Information Processing at DA-IICT
- Coding theory and its applications to natural information processing such as bio-molecular computing, biological information processing and other aspects of information and communication technology (ICT).
- 188
- Error Correcting Codes Page
- Programs written in C/C++ and Matlab that implement encoding and decoding routines of popular error correcting codes. Collected by Robert Morelos-Zaragoza.
- 190
- Covering Codes
- The best known bounds on the size of binary covering codes of length up to 33 and covering radius up to 10. Compiled by Simon Litsyn.
- 191
- Dense Sphere Packings from New Codes
- A table with the largest densities of sphere packings known to us in dimensions up to 200.
- 193
- Tables of Binary Block Codes
- Tables of bounds on the size of binary unrestricted codes, constant-weight codes, doubly-bounded-weight codes, and doubly-constant-weight codes. Compiled by Erik Agrell, Chalmers.
- 198
- Turbo Code
- Information from Wikipedia on these error correction codes developed in 1993 which are finding use in deep space satellite communications and other applications where designers seek to achieve maximal information transfer over a limited-bandwidth communication link in the presence of data-corrupting noise.