【24h】

Efficient BP Algorithms for General Feedforward Neural Networks

机译:通用前馈神经网络的高效BP算法

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

The goal of this work is to present an efficient implementation of the Backpropagation (BP) algorithm to train Artificial Neural Networks with general feedforward topology. This will lead us to the "consecutive retrieval problem" that studies how to arrange efficiently sets into a sequence so that every set appears contiguously in the sequence. The BP implementation is analyzed, comparing efficiency results with another similar tool. Together with the BP implementation, the data description and manipulation features of our toolkit facilitates the development of experiments in numerous fields.
机译:这项工作的目标是提出一种有效的反向传播(BP)算法,以训练具有常规前馈拓扑的人工神经网络。这将导致我们遇到“连续检索问题”,该问题研究如何有效地将集合排列到序列中,以便每个集合在序列中连续出现。分析了BP实施,将效率结果与另一个类似工具进行了比较。与BP实施一起,我们工具包的数据描述和操作功能有助于在许多领域进行实验的开发。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号