| 引用本文: | 杨宜民 ， 章 云， 毛宗源， 周其节.模糊基函数网络辨识算法稳定性*[J].控制理论与应用,1998,15(5):790~793.[点击复制] |
| YANG Yimin，ZHANG Yun， MAO Zongyuan and ZHOU Qijie.Identification Stability on Fuzzy Basis Function Network[J].Control Theory and Technology,1998,15(5):790~793.[点击复制] |
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| 模糊基函数网络辨识算法稳定性* |
| Identification Stability on Fuzzy Basis Function Network |
| 摘要点击 931 全文点击 428 投稿时间：1997-04-11 修订日期：1997-09-10 |
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| DOI编号 |
| 1998,15(5):790-793 |
| 中文关键词 模糊系统 神经网络 持续激励 稳定性 |
| 英文关键词 fuzzy system neural network persistency of excition stability |
| 基金项目 |
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| 中文摘要 |
| 模糊基函数网络能很好地以“小…then…”形式利用专家的知识，且以这种模型进行辨识，其辨识误差方程与辨识参数成线性关系，因而非常适用于实时辨识系统中，本文研究了这种网络模型辨识的持续激励条件和基于梯度法的辨识系统稳定性，给出了它们存在的充要条件. |
| 英文摘要 |
| Linguistic fuzzy IF-THEN rules can often be obtained from human experts who are familiar with the system under consideration. A fuzzy basis function relates to a linguistic fuzzy IF-THEN rule. ln ad-dtion，this fuzzy basis function expansion is linear in its adjustable parameters. Therefore，The fuzzy basis function network is fit to be used as an adaptive identifier. This paper deals with the identification stability，A persistently exciting condition must be satisfied in order to guarantee parameter convengence in the adaptive identifier. Moreover，a sufficient and necessary test between the persistently exciting condition and fuzzy basis functins is given. |