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一种量子竞争学习算法 被引量:6

A Quantum Competitive Learning Algorithm
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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
关键词 量子竞争学习算法 量子计算 HAMMING神经网络 量子神经计算 QCLA quantum learning quantum computation Hamming neural network quantum neural computation
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共引文献23

同被引文献43

  • 1杨俊安,邹谊,庄镇泉.基于多宇宙并行量子遗传算法的非线性盲源分离算法研究[J].电子与信息学报,2004,26(8):1210-1217. 被引量:10
  • 2解光军,范海秋,操礼程.一种量子神经计算网络模型[J].复旦学报(自然科学版),2004,43(5):700-703. 被引量:18
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