摘要
以通用量子门组(即相移门和受控非门)作为基本的计算单元,构造出全新的量子神经元模型,并由此组成前馈型结构网络.仿真结果表明,就文中算例而言,该量子神经网络的计算性能优于传统的神经网络.
Abstract Quantum computation is well known for its particular computational performance. In this paper, a novel quantum neuron model is constructed based on the universal quantum gates unit (i.e. phase-shift gate and controlled-NOT gate), which acts as the basic computational component, with this type of neuron a feed-forward network structure is also built. The simulation results show that the quantum neuron network is superior to classical BP and RBF network for two financial data analysis examples.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2005年第5期113-117,共5页
Systems Engineering-Theory & Practice
基金
国家自然科学基金(60302014)
安徽省自然科学基金(03042202)
中国博士后科学基金(20040350578)
关键词
量子计算
量子神经网络
量子门
quantum computation
quantum neural network
quantum gates
