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A neurocomposition method for extraction of principal components of stochastic processes

机译:一种提取随机过程主要成分的神经组合方法

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A neurocomputation method with an APEX (adaptive principal components extraction) algorithm has recently been proposed by S.Y. Kung and K.I. Diamantaras (1990). In the present work, an improved method with an algorithm called OPEX is presented. It was shown by simulation that OPEX is more robust and has a shorter convergence time than APEX when small eigenvalues are present and the autocorrelation matrix of the input process is ill conditioned.
机译:S.Y.最近提出了一种采用APEX(自适应主成分提取)算法的神经计算方法。功和基爱Diamantaras(1990)。在当前的工作中,提出了一种具有称为OPEX的算法的改进方法。通过仿真表明,当特征值较小且输入过程的自相关矩阵条件不佳时,OPEX比APEX更为健壮,收敛时间更短。

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