量子神经网络与神经网络在信号识别中的对比

Third International Conference on Information Technology and Applications (ICITA'05) Pub Date : 2005-07-04 DOI:10.1109/ICITA.2005.228

Xin-Yi Tsai, Yu-Ju Chen, Huang-Chu Huang, Shang-Jen Chuang, R. Hwang

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引用次数: 17

摘要

本文对利用量子神经网络(QNN)进行信号识别进行了研究和仿真。由于QNN隐含单元的结构，使得分布在两种不同类型信号边界上的模糊信号能够被有效识别。为了验证QNN的识别能力，对二维(NC2)非凸系统中的信号进行了仿真。并与传统神经网络(NN)进行了比较。

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Quantum NN vs. NN in signal recognition

In this paper, the signal recognition by using quantum neural network (QNN) is studied and simulated. The signals with fuzziness distributed in the boundary of two different types of signals could be effectively recognized due to the structure of QNN's hidden units. To demonstrate the capability of QNN in recognition, the signals in a two-dimension (NC2) non-convex system is simulated. All the experiments are also performed by using the traditional neural network (NN) for a comparison.

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Third International Conference on Information Technology and Applications (ICITA'05)

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