首页> 外文会议>Mediterranean Conference on Embedded Computing >Gradient-Descent Algorithm Performance With Reduced Set of Quantized Measurements
【24h】

Gradient-Descent Algorithm Performance With Reduced Set of Quantized Measurements

机译:减少量化测量集的梯度下降算法性能

获取原文

摘要

The quantization (digitalization) of measurements greatly affects the reconstruction performance, especially in algorithms based on the reconstruction in the measurement domain. However, it provides a significant advantage in the hardware implementation sense. In this paper, we analyze the performance of the gradient-based algorithm in the signal reconstruction based on a reduced set of digital measurements. This algorithm is considered as a powerful tool for the reconstruction of various types of signals. The paper investigates the accuracy of the algorithm using B-bit quantized measurements. The reconstruction performance is analyzed through numerical examples.
机译:测量的量化(数字化)极大地影响了重建性能,尤其是在基于测量域中重建的算法中。但是,它在硬件实现方面提供了显着的优势。在本文中,我们基于减少的数字测量集,分析了基于梯度的算法在信号重建中的性能。该算法被认为是用于重构各种类型信号的强大工具。本文研究了使用B位量化测量的算法的准确性。通过数值算例分析了重建性能。

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