数字神经网络在线测试

S. Demidenko, V. Piuri
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引用次数: 5

摘要

在线测试是任何并发容错策略的基本问题。神经网络中的错误定位是为硬件重构提供信息以实现系统生存所必需的。本文讨论并评估了一种数字神经网络中的并发误差定位方法。应用了两种技术:在神经元水平上使用数据编码进行错误检测的并发诊断和网络中故障神经元的在线定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-line testing in digital neural networks
On-line testing is a basic issue of any concurrent fault-tolerance policy. Error localisation within the neural network is necessary to provide information for hardware reconfiguration in order to achieve the system survival. In this paper, a concurrent approach for error localisation in digital neural networks is discussed and evaluated. Two techniques are applied: concurrent diagnosis with the use of data coding for error detection at neuron level and on-line localisation of the faulty neuron within the network.
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