Failure of outer-product learning to perform higher-order ma

机译：外部产品学习无法执行高阶学习

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Abstract: Outer-product learning (also referred to as Hebbian learning) has been used as a very simple training algorithm for neural networks. Outer-product learning also has been proposed as a method for training a network with higher-order interconnections. It is shown in this paper that outer-product learning is inappropriate for higher-order networks because it does not have the ability to perform a non-monotonic mapping.!4

机译：摘要：外部产品学习（也称为Hebbian学习）已被用作神经网络的一种非常简单的训练算法。还提出了产品外学习作为训练具有高阶互连的网络的方法。本文表明，外部产品学习不适用于高阶网络，因为它不具有执行非单调映射的能力！4

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《Infrared Sensors: Detectors, Electronics, and Signal Processing》|1991年|p.187-198|
会议地点 San Diego CA(US);San Diego CA(US)
作者
Jason M. Kinser; Teledyne Brown Engineering; Huntsville; AL; USA.;
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正文语种 eng
中图分类无线电电子学、电信技术;
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Failure of outer-product learning to perform higher-order ma

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