提出一种基于量子纠缠的联想记忆神经网络(QuEAM).对比传统的联想记忆网络,QuEAM的存储容量得到了指数级的增大.学习算法是根据纠缠量度的性质,采用Grover量子迭代算法的基本原理局域放大量子位(qubit)的概率振幅,相当于传统计算机的按位操作,讨论了这个学习算法下的量子基本原理.最后给出具体的例子说明了算法的有效性.
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