Recognition of Continuous Digits by Quantum Neural Networks  

作　　者：LI Fei, ZHAO Sheng-mei, ZHENG Bao-yu (Institute of Signal & Information Processing, Nanjing University of Posts and Telecommunications, Nanjing 210003, P.R. China) 

出　　处：《The Journal of China Universities of Posts and Telecommunications》2003年第1期29-33,共5页中国邮电高校学报（英文版）

基　　金：theScienceandTechnologyFoundationoftheEducationDepartmentofJiangsuProvince (No.2 0 0 1 1 9)

摘　　要：This paper describes a new kind of neural network-Quantum Neural Network(QNN) and its application to recognition of continuous digits. QNN combines the advantages of neuralmodeling and fuzzy theoretic principles . Experiment results show that more than 15 percent errorreduction is achieved on a speaker-independent continuous digits recognition task compared with BPnetworks.This paper describes a new kind of neural network-Quantum Neural Network(QNN) and its application to recognition of continuous digits. QNN combines the advantages of neuralmodeling and fuzzy theoretic principles . Experiment results show that more than 15 percent errorreduction is achieved on a speaker-independent continuous digits recognition task compared with BPnetworks.

关 键 词：quantum neural net-work quantum neuron speech recognition 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]