An Artificial Neural Network Classification Model Based on DNA Computing

Abstract

In this paper, artificial neural network is used to establish an unified model of DNA computing to solve their classification. The main feature of this model is that the idea it uses is parallel logic completely different from traditional computer neural network, that is, for the traditional neural network model, the weights between neurons and neurons are ultimately stable by continuously adjusting, and the adjustment process is a serial, and in the parallel DNA computing model, the weights are determined by finding a set of weights from all possible ones that are suited to all samples. This greatly accelerates the speed of calculation, and the analysis shows that our proposed parallel neural network model is superior to the traditional serial processing.