基于TSK和小波神经模糊模型的非线性动态对象识别与预测

2006 3rd International IEEE Conference Intelligent Systems Pub Date : 2006-09-01 DOI:10.1109/IS.2006.348490

A. Banakar, M. Azeem

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引用次数: 7

摘要

辨识问题包括建立合适的参数化辨识模型，并通过优化性能指标来调整模型的参数。采用并联和并联串联辨识方法对未知模型参数进行调整。本文提出了一种基于TSK模糊模型和小波神经模糊模型的并联/串并联组合辨识模型

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Identification and Prediction of Nonlinear Dynamical Plants Using TSK and Wavelet Neuro-Fuzzy Models

The problem of identification consists of setting up a suitably parameterized identification model and adjusting the parameters of the model by optimizing a performance index. Parallel and parallel-series identification methods are used to adjust an unknown model's parameters. In this paper a combined parallel/series-parallel identification model, based on TSK fuzzy model and wavelet neuro-fuzzy model, is proposed

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2006 3rd International IEEE Conference Intelligent Systems

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