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2009 WRI World Congress on Computer Science and Information Engineering
HAMFAST: Fast Hamming Distance Computation
Los Angeles, California USA
March 31April 02
ISBN: 9780769535074
ASCII Text  x  
Francesco Pappalardo, Cristiano Calonaci, Marzio Pennisi, Emilio Mastriani, Santo Motta, "HAMFAST: Fast Hamming Distance Computation," Computer Science and Information Engineering, World Congress on, vol. 1, pp. 569572, 2009 WRI World Congress on Computer Science and Information Engineering, 2009.  
BibTex  x  
@article{ 10.1109/CSIE.2009.223, author = {Francesco Pappalardo and Cristiano Calonaci and Marzio Pennisi and Emilio Mastriani and Santo Motta}, title = {HAMFAST: Fast Hamming Distance Computation}, journal ={Computer Science and Information Engineering, World Congress on}, volume = {1}, year = {2009}, isbn = {9780769535074}, pages = {569572}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.223}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  CONF JO  Computer Science and Information Engineering, World Congress on TI  HAMFAST: Fast Hamming Distance Computation SN  9780769535074 SP569 EP572 A1  Francesco Pappalardo, A1  Cristiano Calonaci, A1  Marzio Pennisi, A1  Emilio Mastriani, A1  Santo Motta, PY  2009 KW  Hamming distance KW  immune system KW  computational modeling KW  algorithms KW  optimization VL  1 JA  Computer Science and Information Engineering, World Congress on ER   
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.223
Similarity is a vague concept which can be treated in a quantitative manner only using appropriate mathematical representation of the objects to compare and a metric on the space representation. In biology the mathematical representation of structure relies on strings taken from an alphabet of m symbols. Very often binary strings, m = 2, are used. The size of the binary string depends on the complexity of the structure to represent, so the string can be quite long. The Hamming distance is the most used metric with binary strings. The computational effort required to compute the Hamming distance linearly depends on the size of the string. However even a linear effort case may be computational heavy if many computations are required. One of the fastest computational approach to evaluate Hamming distances relies on lookup tables. The computational performance, however, rapidly deteriorates with the size of binary string length, due to cache misses. We present a computational strategy and implementation which can handle huge number of Hamming distance evaluation between binary strings of arbitrary length keeping computational performance competitive.
Index Terms:
Hamming distance, immune system, computational modeling, algorithms, optimization
Citation:
Francesco Pappalardo, Cristiano Calonaci, Marzio Pennisi, Emilio Mastriani, Santo Motta, "HAMFAST: Fast Hamming Distance Computation," csie, vol. 1, pp.569572, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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