| 1. | Pattern learning with the back - propagation algorithm
利用反向传播算法的模式学习 |
| 2. | Moreover , the basic outline of a back - propagation algorithm runs like this
关于反向传播算法的基本情况大致如此。 |
| 3. | Back propagation algorithm
反传算法 |
| 4. | Design of on - line learning based error back propagation algorithm in simulation servo system
基于在线学习误差反传算法的仿真伺服系统设计 |
| 5. | The back - propagation algorithm and its program of the rough neuron network are presented
本文同时给出了粗神经网络bp算法和用粗神经网络预测上证指数的程序。 |
| 6. | A comparison of two constraint propagation algorithms and an improved algorithm for disjunctive scheduling problem
调度问题中两类分离约束传播算法的比较及一种改进算法 |
| 7. | The multilayer perception , trained by the back propagation algorithm , is currently the most widely used neural network
Bp神经网络是目前神经网络理论发展最完善、应用最为广泛的网络。 |
| 8. | Finally , i realize and optimize two algorithms : apriori algorithm and back - propagation algorithm
最后，本文对数据挖掘的两种基本算法： apriori算法和b - p算法的计算机实现与优化做了探讨。 |
| 9. | With the back - propagation algorithm in hand , we can turn to our puzzle of identifying the language of source code samples
在掌握了反向传播算法后，可以来看我们的识别源代码样本语言的难题。 |
| 10. | Aiming at the multi replication definition , the thesis presents three optimized propagation algorithms : d - m , ils and lis
针对多重复制定义现象，本文提出三个最优传播算法： d - m 、 ils和lis 。 |
