Reviewers
|
Book & Monographs
|
Conference
|
Contact Us
SEARCH
|
My Profile
|
My Shopping Cart
|
Logout
Home
Publication Ethics
Open Access Policy
Guidelines
Journals
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
Submit a Manuscript
Author Login
Author Registration
Forget Password
Journal Menu
Journal Home
Editorial Board
Guidelines for Authors
Indexing
Contents
Contents
Subscribe
Publication Ethics and Publication Malpractice Statement
Content
Volume 19 (2022)
Volume 19, (In Progress)
Pg 1 - 11 (June 2022)
Volume 18 (2019)
Volume 18, Issue 1
Pg 1 - 37 (June 2019)
Volume 17 (2018)
Volume 17, Issue 2
Pg 55 - 74 (December 2018)
Volume 17, Issue 1
Pg 1 - 54 (June 2018)
Volume 16 (2016)
Volume 16, Issue 3-4
Pg 61 - 101 (November 2016)
Volume 16, Issue 1-2
Pg 1 - 60 (May 2016)
Volume 15 (2015)
Volume 15, Issue 1-2
Pg 1 - 55 (November 2015)
Volume 14 (2015)
Volume 14, Issue 2
Pg 59 - 109 (May 2015)
Volume 14, Issue 1
Pg 1 - 57 (February 2015)
Volume 13 (2014)
Volume 13, Issue 2
Pg 73 - 152 (November 2014)
Volume 13, Issue 1
Pg 1 - 72 (August 2014)
Volume 12 (2014)
Volume 12, Issue 2
Pg 61 - 128 (May 2014)
Volume 12, Issue 1
Pg 1 - 60 (February 2014)
Volume 11 (2013)
Volume 11, Issue 2
Pg 51 - 107 (November 2013)
Volume 11, Issue 1
Pg 1 - 50 (August 2013)
Volume 10 (2013)
Volume 10, Issue 2
Pg 77 - 131 (May 2013)
Volume 10, Issue 1
Pg 1 - 76 (February 2013)
Volume 9 (2012)
Volume 9, Issue 2
Pg 83 - 159 (November 2012)
Volume 9, Issue 1
Pg 1 - 82 (August 2012)
Volume 8 (2012)
Volume 8, Issue 2
Pg 69 - 145 (May 2012)
Volume 8, Issue 1
Pg 1 - 67 (February 2012)
Volume 7 (2011)
Volume 7, Issue 2
Pg 99 - 168 (November 2011)
Volume 7, Issue 1
Pg 1 - 97 (August 2011)
Volume 6 (2011)
Volume 6, Issue 2
Pg 105 - 204 (May 2011)
Volume 6, Issue 1
Pg 1 - 104 (February 2011)
Volume 5 (2010)
Volume 5, Issue 2
Pg 131 - 263 (November 2010)
Volume 5, Issue 1
Pg 1 - 129 (August 2010)
Volume 4 (2010)
Volume 4, Issue 2
Pg 93 - 184 (May 2010)
Volume 4, Issue 1
Pg 1 - 92 (February 2010)
Volume 3 (2009)
Volume 3, Issue 3
Pg 175 - 266 (November 2009)
Volume 3, Issue 2
Pg 87 - 174 (July 2009)
Volume 3, Issue 1
Pg 1 - 85 (March 2009)
Volume 2 (2008)
Volume 2, Issue 3
Pg 201 - 284 (November 2008)
Volume 2, Issue 2
Pg 97 - 199 (July 2008)
Volume 2, Issue 1
Pg 1 - 96 (March 2008)
Volume 1 (2007)
Volume 1, Issue 3
Pg 189 - 283 (November 2007)
Volume 1, Issue 2
Pg 105 - 187 (July 2007)
Volume 1, Issue 1
Pg 1 - 104 (March 2007)
Categories
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
Advances in Computer Science and Engineering
Advances in Computer Science and Engineering
Volume 3, Issue 2, Pages 111 - 125 (July 2009)
DESIGNING BINARY LINEAR BLOCK CODES WITH SPECIFIED MINIMUM WEIGHT USING SIMULATED ANNEALING
Wasan S. Awad (Bahrain)
Abstract:
Controlling errors in the communication system can be performed by means of the application of special codes that add redundancy. These codes can detect and/or correct errors occurred during the data transmission. In this work, we focus on a class of error correcting codes which is binary linear block codes. The problem of finding an error correcting code that corrects a maximum number of errors with as few as possible number of redundant bits is NP-complete problem. For this reason, genetic algorithm and simulated annealing have been chosen in this work to solve the problem of designing error correcting codes. In this paper, two algorithms will be presented for finding the generator matrix of a linear block code with specified error detection/correction capability. The implementation and results of applying these algorithms will be also presented.
Keywords and phrases:
simulated annealing, genetic algorithm, linear block codes, minimum weight.
Number of Downloads:
280 |
Number of Views:
875
Previous
Next
P-ISSN: 0973-6999
Journal Stats
Publication count:
171
Citation count (Google Scholar):
0
h10-index (Google Scholar):
0
h-index (Google Scholar):
0
Downloads :
53520
Views:
143941
Downloads/publish articles:
312.98
Citations (Google Scholar)/publish articles:
0
This website is best viewed at 1024x768 or higher resolution with Microsoft Internet Explorer 6 or newer.
