具有不可测量状态变量的动态系统的神经建模

IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings Pub Date : 1997-05-19 DOI:10.1109/IMTC.1997.612371

C. Alippi, V. Piuri

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引用次数: 8

摘要

本文研究动态过程的神经模型。重点研究了以不可测量状态为特征的过程及其非线性递归神经网络建模。对于这种模型，建立了一种将实际预测误差与过去预测误差相关联的关系。

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Neural modelling of dynamic systems with non-measurable state variables

The paper deals with neural modelling of dynamic processes. Attention is focused on processes characterised by non-measurable states and their modelling with nonlinear recurrent neural networks. A relationship is developed which, for such models, correlates the actual prediction error with the past ones.

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IEEE Instrumentation and Measurement Technology Conference Sensing, Processing, Networking. IMTC Proceedings

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