电子测试
電子測試
전자측시
ELECTRONIC TEST
2012年
5期
7-12
,共6页
量子神经网络%BP算法%量子BP算法%图像压缩
量子神經網絡%BP算法%量子BP算法%圖像壓縮
양자신경망락%BP산법%양자BP산법%도상압축
quantum neural network%back-propagation algorithm%quantum back-propagation algorithm%imagecompressing
量子神经网络是一门崭新的学科,是量子理论和人工神经网络结合的产物。它融合了量子计算与神经网络的优点,具有很高的理论价值和应用潜力。本文基于具有量子输入和量子输出的量子神经元模型,利用BP网络用于图像压缩的原理,同时借助复数BP算法提出了QBP算法,构建一种用于图像压缩的3层QBP网络模型,实现了图像压缩与图像重建。仿真结果表明,在与BP网络压缩比相同的情况下,QBP网络不仅获取较好的重建图像质量,而且在最佳学习速率下迭代次数比BP网络少。
量子神經網絡是一門嶄新的學科,是量子理論和人工神經網絡結閤的產物。它融閤瞭量子計算與神經網絡的優點,具有很高的理論價值和應用潛力。本文基于具有量子輸入和量子輸齣的量子神經元模型,利用BP網絡用于圖像壓縮的原理,同時藉助複數BP算法提齣瞭QBP算法,構建一種用于圖像壓縮的3層QBP網絡模型,實現瞭圖像壓縮與圖像重建。倣真結果錶明,在與BP網絡壓縮比相同的情況下,QBP網絡不僅穫取較好的重建圖像質量,而且在最佳學習速率下迭代次數比BP網絡少。
양자신경망락시일문참신적학과,시양자이론화인공신경망락결합적산물。타융합료양자계산여신경망락적우점,구유흔고적이론개치화응용잠력。본문기우구유양자수입화양자수출적양자신경원모형,이용BP망락용우도상압축적원리,동시차조복수BP산법제출료QBP산법,구건일충용우도상압축적3층QBP망락모형,실현료도상압축여도상중건。방진결과표명,재여BP망락압축비상동적정황하,QBP망락불부획취교호적중건도상질량,이차재최가학습속솔하질대차수비BP망락소。
Quantum Neural Network (QNN), which integrates the characteristics of Artificial Neural Network (ANN) with quantum theory, is a new study field. It takes advantages of ANN and quantum computing and has a high theoretical value and potential applications. Based on quantum neuron model with a quantum input and output quantum and artificial neural network theory, at the same time, QBP algorithm is proposed on the basis of the complex BP algorithm, the network of a 3-layer quantum BP which implements image compression and image reconstruction is built. The simulation results show that QBP can obtain the reconstructed images with better quantity compared with BP in spite of the less learning iterations.