Harmonic Retrieval from Coarsely Quantized Measurements.

ACSCC(2021)

引用 2|浏览0
暂无评分
摘要
We consider the problem of harmonic retrieval from coarsely quantized measurements. We formulate the sinusoidal parameter estimation problem into a sparse parameter estimation problem by adding an l q -norm (0 < q ≤ 1) based penalty term to the negative log-likelihood function. A user parameter-free algorithm is devised to solve the problem efficiently by using the cyclic optimization and majorization-minimization (MM) techniques. Numerical examples are provided to demonstrate the estimation performance of the proposed algorithm.
更多
查看译文
关键词
Harmonic retrieval,coarsely quantized measurements,sparse parameter estimation,majorization-minimization (MM)
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要