International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 106 - Issue 10 |
Published: November 2014 |
Authors: B. Suribabu Naick, P. Rajesh Kumar |
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B. Suribabu Naick, P. Rajesh Kumar . Detection of Low Auto Correlation Binary Sequences using Meta Heuristic Approach. International Journal of Computer Applications. 106, 10 (November 2014), 32-37. DOI=10.5120/18560-9824
@article{ 10.5120/18560-9824, author = { B. Suribabu Naick,P. Rajesh Kumar }, title = { Detection of Low Auto Correlation Binary Sequences using Meta Heuristic Approach }, journal = { International Journal of Computer Applications }, year = { 2014 }, volume = { 106 }, number = { 10 }, pages = { 32-37 }, doi = { 10.5120/18560-9824 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2014 %A B. Suribabu Naick %A P. Rajesh Kumar %T Detection of Low Auto Correlation Binary Sequences using Meta Heuristic Approach%T %J International Journal of Computer Applications %V 106 %N 10 %P 32-37 %R 10.5120/18560-9824 %I Foundation of Computer Science (FCS), NY, USA
This paper describes the method that constructs low autocorrelation binary sequences (LABS) which have applications in various engineering domains. We use a meta-heuristic search approach employing local search method known as Tabu Search, which solves mathematical optimization problems. Our paper is an extension to the existing one [1]. We were able to achieve new optimal solutions with our improved algorithm (especially for instances greater than 60 and less than 101) to that of the previous method [1]. Instead of finding optimal solutions for odd skew- symmetric instances we found the optimal solutions for all the instances. We have conducted experiments over a large number of sequences thoroughly, for multiple times to ensure the results.