摘要
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 is well known for its particular computational performance. In this paper, we try to combine quantum computation with classical neural computation, through designing several quantum operators we construct the quantum counterpart of Hamming neural network, and put forward a quantum competitive learning algorithm to realize functions of pattern classification and associative memory.
出处
《量子电子学报》
CAS
CSCD
北大核心
2003年第1期42-46,共5页
Chinese Journal of Quantum Electronics
基金
国家自然科学基金(60171029)资助