| 1. | Application of k - l transformation the optimization of initial weights of bp neural network
网络初始权值优化中的应用 |
| 2. | Nntcs employs genetic algorithm ( ga ) in the stage of training to optimize initial weights of ann
训练过程中结合遗传算法，优化神经网络的初始权值。 |
| 3. | Genetic algorithm is used to optimize the initial weight of back propagation network and the operation efficiency is enhanced
用遗传算法优化bp网络的初始权值,提高神经网络的运算速度。 |
| 4. | The initial weights of the neural network can be given according to the material meaning , which expedites the network convergence
文中将神经网络与ip控制器结合，权的初始值可据其意义设定，大大加快了网络的收敛速度。 |
| 5. | In the control process uses two bp network . one is used as nni recognizing the model , another as neural network control device ( nnc ) . but first off - line recognizes controlled device , make sure nnc initial weights
在控制的过程中,采用两个bp网络,一个作为神经网络辨识器( nni )进行辨识建模;另一个作为神经网络控制器( nnc ) 。 |
| 6. | The algorithms for training weights update and constructing the target vectors are discussed . use the penalty term to improve the astringency of network . and study how choice the appropriate initial weights
着重研究了根据输入和输出量合理选择网络结构,训练权值的更新算法,目标向量的合理构造,带惩罚项的bp网络,改善了网络的收敛性。 |
| 7. | The dependences in multitemporal multispectral images by independent component analysis are reduced . in the algorithm , damped factor is imported to reduce the dependence on initial weights , thus the robust of the algorithm is improved
在改进的独立成分学习算法中,通过在梯度下降方法中引入阻尼因子,降低了对初始值的依赖,提高了独立成分求解的稳健性。 |
| 8. | During the course of develop fault diagnostic method , the influence to the training circle number with network structure 、 learning rate 、 initial weight value & door value etc are discussed . by comprehensive analyses and comparing , the comparatively rational value is adopted to be network ' s eigenvalue
在制粉系统故障诊断样本训练过程中，本文作者探讨了网络结构、学习率、初始权值阈值等因素对训练速度的影响，为选取合理的网络参数提供了依据。 |
