| 引用本文: | 李世华,吴福保,李 奇.一种基于动态人工神经网络的Wiener模型辨识[J].控制理论与应用,2000,17(1):92~95.[点击复制] |
| LI Shi-hua,WU Fu-bao,LI Qi.Identification of Wiener Model Using Dynamic Artificial Neural Networks[J].Control Theory and Technology,2000,17(1):92~95.[点击复制] |
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| 一种基于动态人工神经网络的Wiener模型辨识 |
| Identification of Wiener Model Using Dynamic Artificial Neural Networks |
| 摘要点击 1377 全文点击 1455 投稿时间：1998-05-04 修订日期：1998-11-11 |
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| DOI编号 10.7641/j.issn.1000-8152.2000.1.022 |
| 2000,17(1):92-95 |
| 中文关键词 人工神经网络 系统辨识 Wiener模型 |
| 英文关键词 neural networks nonlinear systems identification Wiener model |
| 基金项目 |
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| 中文摘要 |
| 提出了一种新的辨识模型对Wiener模型进行辨识.该模型由一线性动态神经元串联一静态BP网络模型组成.利用线性动态神经元对Wiener模型的线性动态部分建模,利用静态BP网络逼近模型的静态非线性部分.并且给出了统一的BP辨识算法.仿真结果表明了该方法的有效性. |
| 英文摘要 |
| The problem of identification of a Wiener model is studied.The proposed identification method uses a dynamic neural network (DANN) which consists of a linear dynamic neuron (LDN) in cascade with a static BP neural network (SBP).A unified back propagation algorithm is proposed to estimate the weights and the biases of the LDN and the SBP simultaneously.Numerical examples are provided to show the efficiency of the proposed method. |