Title :
A DNA Computing Model of Perceptron
Author :
Liu, Wei ; Sun, Shouxia ; Guo, Ying
Author_Institution :
Coll. of Math. & Inf., LuDong Univ., Yantai, China
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;
Conference_Titel :
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3614-9
DOI :
10.1109/PACCS.2009.182
