摘要
本文给出实时求解正定矩阵最小和最大特征值对应特征矢量的神经网络模型。文中的理论分析和模拟结果表明：网络能在电路时常数数量级内给出所求的解，网络给出的解与准确的特征矢量可以任意接近。
This paper presents a neural network approach to computing the eigenvectors corresponding to tae largest and smallest eigenvalues of a positive matrix. We show both analytically and by simulation results that this proposed network is guaranteed to provide the results arbitrarily close to the accurate eigenvectors within an elapsed time of only a few characteristic time constants of the network.
出处
《电子学报》
EI
CAS
CSCD
北大核心
1994年第4期13-19,共7页
Acta Electronica Sinica
基金
攀登计划资助
国家自然科学基金
关键词
神经网络
信号处理
特征值
矩阵
Neural networks,Signal processing,Matrix computation
