.png){kind=icon}
返回
Performance evaluation and parameter optimization of sparse Fourier transform
.png){kind=icon}
PRE
AI
DOI：10.1016/j.sigpro.2020.107823.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The sparse Fourier transform (SFT) dramatically accelerates spectral analyses by leveraging the inherit sparsity in most natural signals. However, a satisfactory trade-off between the estimation performance and the computational complexity commonly requires sophisticated empirical parameter tuning. In this work, we attempt to further enhance SFT by optimizing the parameter selection mechanism. We first derive closed-form expressions of objective performance metrics. On top of this, a parameter optimization algorithm is designed to minimize the complexity, under the premise that the performance metrics can meet the specified requirements. The proposed scheme, termed as optimized SFT, is shown to be able to automatically determine the optimized parameter settings as per the a priori knowledge and the performance requirements in the numerical simulations. Experimental studies of continuous-wave radar detection are also conducted to demonstrate the potential of the optimized SFT in the practical application scenarios. (C) 2020 Elsevier B.V. All rights reserved.
Keyword:
Sparse fourier transform
Digital signal processing
Numerical algorithms
Radar target detection
Time-frequency analysis
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
10.0K
被引数:
1.7W
机构
引用论文
Cooperative Wideband Spectrum Sensing Based on Sub-Nyquist Sparse Fast Fourier Transform基于亚奈奎斯特稀疏快速傅里叶变换的协作宽带频谱感知
.png){kind=icon}
PREAI
分享收藏分享收藏FT‐Raman and surface‐enhanced Raman scattering (SERS) spectroscopic study of a methyl red@palygorskite hybrid nanocomposite: isomerization and protonation of the guest dyeFT‐Raman和表面增强拉曼散射(SERS)光谱学研究甲基红@坡缕石杂化纳米复合材料：客体染料的异构化和质子化
OAAI
OAAI分享收藏
查看更多内容