...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Sensors Journal, IEEE >A Deep Learning-Based Compression Algorithm for 9-DOF Inertial Measurement Unit Signals Along With an Error Compensating Mechanism
【24h】

A Deep Learning-Based Compression Algorithm for 9-DOF Inertial Measurement Unit Signals Along With an Error Compensating Mechanism

机译：基于深度学习的9自由度惯性测量单元信号压缩算法以及误差补偿机制

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Inertial sensors with microelectromechanical systems technology are an integral part of many modern electronic devices such as wearable medical products, which are inherently subject to memory, bandwidth, and energy constraints due to their size and purpose. One of the important challenges for the progress in this area is the storage, transmission, and processing of large quantities of inertial sensors signal. To address this issue, this paper presents a method for near-lossless compression of multi-axis inertial signals. To improve the inertial signal compression capability, the proposed compression method employs the independent component analysis method with a principal component analysis preprocessing step to extract independent components from the signals. A deep autoencoder is used to compress the independent components and later to estimate them in the reconstruction phase. The reconstruction error is also quantized and coded using arithmetic coding and transmitted alongside the compressed components. This paper also proposes a new approach for improving the quality of the reconstructed signals. In this approach, on the receiver side, the reconstruction error is fed to the Madgwick filter as an external noise and is compensated using this filter. The experimental results demonstrate the high compression rate and low reconstruction error of the proposed method compared to the state-of-the-art methods.
机译：具有微机电系统技术的惯性传感器是许多现代电子设备（如可穿戴医疗产品）不可或缺的一部分，由于其尺寸和用途，它们固有地受到内存，带宽和能量的限制。在这一领域取得进展的重要挑战之一是大量惯性传感器信号的存储，传输和处理。为了解决这个问题，本文提出了一种多轴惯性信号的近无损压缩方法。为了提高惯性信号的压缩能力，提出的压缩方法采用了独立分量分析方法和主分量分析预处理步骤，以从信号中提取独立分量。深度自动编码器用于压缩独立分量，然后在重建阶段对其进行估计。还使用算术编码对重建误差进行量化和编码，并与压缩分量一起传输。本文还提出了一种改善重构信号质量的新方法。在这种方法中，在接收器端，重建误差作为外部噪声被馈送到Madgwick滤波器，并使用该滤波器进行补偿。实验结果表明，与最新方法相比，该方法具有较高的压缩率和较低的重建误差。

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