RBF神经网络梯度法

RBF神经网络梯度法是一种用于调节RBF神经网络参数的学习算法。在RBF网络设计中，采用梯度下降法调节RBF网络的参数，包括中心点(cj)和标准差(b)的值，以实现RBF网络的有效学习。通过梯度下降法，根据网络输出与期望输出之间的误差，反向传播误差信号并调整参数值，以逐步减小误差，提高网络的逼近能力和拟合性能。通过这种方式，RBF神经网络可以逼近未知部分的模型，并用于控制和预测等任务。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [笔记(待续)-基于梯度下降法的RBF神经网络控制](https://blog.csdn.net/weixin_41235419/article/details/115654502)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *2* [rbf神经网络参数设置_基于梯度下降法的RBF神经网络逼近（03）](https://blog.csdn.net/weixin_39575007/article/details/110217969)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *3* [RBF神经网络](https://blog.csdn.net/fqianqian96/article/details/129015336)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
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