• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Engineering MIS >Generic neural architecture for LVQ artificial neural networks
【24h】

Generic neural architecture for LVQ artificial neural networks

机译：LVQ人工神经网络的通用神经架构

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper reports an approach for the implementation of learning vector quantization (LVQ) neural network with different generic architectures and a reduction of the latency. Our approach is based on a hardware/software design (HW/SW) for on-chip and on-line learning with generic architectures. It is based, as well, on a variable topology (the number of neurons in the hidden layer and the number of entries are scalable) that makes it generic and usable for many applications without hardware modifications. In this contribution, we have integrated the parallelism rate into the data path, which is responsible for calculating the minimum distance, weights and labels, in order to solve problems of application latency. Therefore, our approach allows a compromise between latency, power and parallelism. These generic architectures allow enlightening the vision of the designers for the right choice of architecture that suits their needs. These different designs can be used for different applications including applications for vigilance states detection, image processing, EEG signals and ECG signals, etc.
机译：本文报告了一种采用不同通用体系结构并减少等待时间的学习矢量量化（LVQ）神经网络的实现方法。我们的方法基于硬件/软件设计（HW / SW），用于具有通用体系结构的片上和在线学习。它也是基于可变拓扑（隐藏层中神经元的数量和条目的数量是可伸缩的）的，这使它通用且可用于许多无需修改硬件的应用程序。在此贡献中，我们已将并行速率集成到数据路径中，该数据路径负责计算最小距离，权重和标签，以解决应用程序延迟问题。因此，我们的方法允许在延迟，功耗和并行度之间进行折衷。这些通用架构可以启发设计师的愿景，以选择适合他们需求的正确架构。这些不同的设计可用于不同的应用，包括警戒状态检测，图像处理，EEG信号和ECG信号等应用。

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