【摘要】 量子计算与人工神经网络相结合的量子神经网络(QNN-Quantum Neural Networks)由于利用了量子并行计 算和量子纠缠等特性从而克服了传统人工神经网络的某些固有缺陷,将成为未来信息处理的重要手段。介绍了与量子神经 网络相关的量子计算基础,描述了一种量子神经元模型,分析证明了单个量子神经元具有与两层前向神经网络相当的非线 性映射能力。提出了一种基于量子神经元与量子寄存器的多用户检测方案,计算机仿真结果表明:本文所提出的检测器在 误码率和抗“远近”效应方面均具有良好的性能。更多还原

【Abstract】 Quantum Neural Networks (QNN) is a new field which integrates ANN with quantum computing. Taking advantages of the properties of quantum mechanics such as quantum parallelism and entanglement, QNN may give us unprecedented possibilities in creating new system for information processing. The fundamental of QNN is introduced and a model for quantum neuron is described. Numerical and graphical results show that this single quantum neuron has the same computational power as the two-layer perceptron, it can obtain nonlinear mapping. A multiuser detector based on quantum neuron and quantum register is proposed. Computer simulation results show that the method has powerful properties both in bit error rate and near-far resistance.更多还原