Quantum generation of neural networks

被引：0

作者：

de Garis, H ^{[1
]}

Sriram, R ^{[1
]}

Zhang, ZJ ^{[1
]}

机构：

[1] Utah State Univ, Dept Comp Sci, Brain Builder Grp, Logan, UT 84322 USA

来源：

PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper shows how the new field of quantum computing can be applied to the creation of neural network circuits. Quantum computing is capable of processing huge numbers of quantum states simultaneously, in parallel, ("quantum parallelism"). In theory, QC ought to be able to process all possible points in a 2(N) search space (of N bit bitstrings). If N is large, 2(N) is gigantic, making a systematic search with a classical computer impossible. This paper presents an extended example of a simple QC algorithm applied to the generation of neural network circuits.

引用

页码：2589 / 2593

页数：5

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