Autonomous DNA Neuron Learning Algorithm Based on DNA Strand Displacement

Xuedong Zheng, Yang Ru
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Abstract

DNA neuron learning, or weight update of DNA neurons, is an important research content in the construction of a DNA neural network. In this work, we propose a DNA reaction network to implement the autonomous weight update of DNA neurons based on DNA strand displacement. The DNA reaction network consists of four modules: weight update module, calculation module, synchronization module, and feedback adjustment module to achieve the effectiveness and consistency of multiple training data in DNA neuron learning. Especially, the learning and the testing of DNA neurons are in the same DNA strand displacement reaction system. The simulation results show that the DNA neuron can classify test data correctly, which proves that the algorithm adopted in this work is effective.
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基于DNA链位移的自主DNA神经元学习算法
DNA神经元的学习,即DNA神经元的权值更新,是构建DNA神经网络的重要研究内容。在这项工作中,我们提出了一个基于DNA链位移的DNA反应网络来实现DNA神经元的自主权更新。DNA反应网络由四个模块组成:权值更新模块、计算模块、同步模块和反馈调整模块,以实现DNA神经元学习中多个训练数据的有效性和一致性。特别是,DNA神经元的学习和测试是在同一个DNA链位移反应系统中进行的。仿真结果表明,DNA神经元能够正确地对测试数据进行分类,证明了本文所采用的算法是有效的。
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