论文部分内容阅读
量子计算(Quantum Computation)以其独特的性能引起广泛瞩目。本文尝试将量子计算与传统的神经计算结合起来,通过设计若干个量子算子来构造Hamming神经网络的量子对照物,从而提出一种量子竞争学习算法(Quantum Competitive Learning Algorithm,QCLA),它能够实现模式分类和联想记忆。
Quantum Computation draws much attention for its unique properties. In this paper, we attempt to combine quantum computing with traditional neural computing to construct a quantum control of Hamming neural network through the design of several quantum operators, so as to propose a Quantum Competitive Learning Algorithm (QCLA) Pattern classification and associative memory.