DocumentCode
3290617
Title
A DNA Computing Model of Perceptron
Author
Liu, Wei ; Sun, Shouxia ; Guo, Ying
Author_Institution
Coll. of Math. & Inf., LuDong Univ., Yantai, China
fYear
2009
fDate
16-17 May 2009
Firstpage
726
Lastpage
729
Abstract
Since Adleman shows that DNA strands can be used to solve an instance of the NP-complete Hamiltonian path problem (HPP). DNA computing has been used to solve all kinds of difficult problems including neural networks. This paper put forward a DNA computing model of perceptron to implement linear categorizer function. The advantage of the DNA computing model is the great parallelism of algorithm which will significant improve the efficiency of perceptron categorizer and reduce the running time of perceptron as the same time.
Keywords
biocomputing; computational complexity; neural nets; optimisation; DNA computing model; NP-complete Hamiltonian path problem; linear categorizer function; neural networks; perceptron categorizer; Artificial neural networks; Circuits; Concurrent computing; DNA computing; Educational institutions; Mathematical model; Mathematics; Neural networks; Parallel processing; Sun; DNA computing; parallelism; perceptron;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location
Chengdu
Print_ISBN
978-0-7695-3614-9
Type
conf
DOI
10.1109/PACCS.2009.182
Filename
5232428
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