TY - JOUR
T1 - Pattern Recognition of mtDNA with Associative Models
AU - Acevedo, María Elena
AU - Acevedo, Marco Antonio
AU - Felipe, Federico
AU - Aquino, David
N1 - Publisher Copyright:
© 2016 The Authors, published by EDP Sciences.
PY - 2016/8/1
Y1 - 2016/8/1
N2 - In this paper we applied an associative memory for the pattern recognition of mtDNA that can be useful to identify bodies and human remains. In particular, we used both morphological hetroassociative memories: max and min. We process the problem of pattern recognition as a classification task. Our proposal showed a correct recall, we obtained the 100% of recalling of all the learned patterns. We simulated a corrupted sample of mtDNA by adding noise of two types: additive and subtractive. The memory showed a correct recall when we applied less or equal than 55% of both types of noise.
AB - In this paper we applied an associative memory for the pattern recognition of mtDNA that can be useful to identify bodies and human remains. In particular, we used both morphological hetroassociative memories: max and min. We process the problem of pattern recognition as a classification task. Our proposal showed a correct recall, we obtained the 100% of recalling of all the learned patterns. We simulated a corrupted sample of mtDNA by adding noise of two types: additive and subtractive. The memory showed a correct recall when we applied less or equal than 55% of both types of noise.
UR - http://www.scopus.com/inward/record.url?scp=84982155959&partnerID=8YFLogxK
U2 - 10.1051/matecconf/20166818002
DO - 10.1051/matecconf/20166818002
M3 - Artículo de la conferencia
AN - SCOPUS:84982155959
SN - 2261-236X
VL - 68
JO - MATEC Web of Conferences
JF - MATEC Web of Conferences
M1 - 18002
T2 - 2016 3rd International Conference on Industrial Engineering and Applications, ICIEA 2016
Y2 - 28 April 2016 through 30 April 2016
ER -