Affiliation:
1. Key Laboratory of Advanced Design and Intelligent Computing, Ministry of Education, Dalian University, Dalian 116622, P. R. China
2. School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, P. R. China
Abstract
The ability of neural networks to process information intelligently has allowed them to be successfully applied in the fields of information processing, controls, engineering, medicine, and economics. The brain-like working mode of a neural network gives it incomparable advantages in solving complex nonlinear problems compared with other methods. In this paper, we propose a feedforward DNA neural network framework based on an enzyme-free, entropy-driven DNA reaction network that uses a modular design. A multiplication gate, an addition gate, a subtraction gate, and a threshold gate module based on the DNA strand displacement principle are cascaded into a single DNA neuron, and the neuron cascade is used to form a feedforward transfer neural network. We use this feedforward neural network to realize XOR logic operation and full adder logic operation, which proves that the molecular neural network system based on DNA strand displacement can carry out complex nonlinear operation and reflects the powerful potential of building these molecular neural networks.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Program for Changjiang Scholars and Innovative Research Team in University
Program for Liaoning Innovative Research Team in University
Natural Science Foundation of Liaoning Province
High-level Talent Innovation Support Program of Dalian City
Dalian Outstanding Young Science and Technology Talent Support Program
Publisher
World Scientific Pub Co Pte Lt
Subject
Condensed Matter Physics,General Materials Science
Cited by
6 articles.
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