匹配追踪
匹配(统计)
残余物
信号(编程语言)
算法
产品(数学)
多径传播
灵敏度(控制系统)
计算机科学
Blossom算法
过程(计算)
质量(理念)
模式识别(心理学)
数学
人工智能
电子工程
工程类
压缩传感
统计
电信
物理
程序设计语言
几何学
频道(广播)
操作系统
量子力学
作者
Menghang Wu,Fei‐Yun Wu,Kunde Yang,Tian Tian
标识
DOI:10.1109/icspcc50002.2020.9259501
摘要
The traditional multipath matching pursuit (MMP) algorithm generally uses inner product matching criteria (IPMc) to select the best atom for signal reconstruction, and often lose some important information of atoms. Therefore, any two similar atoms of the observation matrix will affect the process of selecting the best atom for the residual signal, and reduce the quality of signal reconstruction. Using the improved inner product matching criteria (I-IPMc) improves the sensitivity of the MMP algorithm to atom values, optimizes the selection of support sets, and reduces the impact of similar atoms on the matching process. The simulation results show that under the same conditions, the MMP algorithm based on the I-IPMc has better reconstruction quality and higher signal reconstruction probability than the traditional MMP algorithm.
科研通智能强力驱动
Strongly Powered by AbleSci AI