小波变换
算法
小波
谐波小波变换
计算机科学
平稳小波变换
噪音(视频)
包络线(雷达)
第二代小波变换
信号(编程语言)
分段
光谱密度
信号处理
数学
离散小波变换
人工智能
数学分析
电信
图像(数学)
程序设计语言
雷达
作者
Cuifang Zhuang,Ping Liao
出处
期刊:IEEE Access
[Institute of Electrical and Electronics Engineers]
日期:2020-01-01
卷期号:8: 24484-24494
被引量:14
标识
DOI:10.1109/access.2020.2968851
摘要
Empirical wavelet transform (EWT) has become an effective tool for signal processing. However, its sensitivity to noise may bring side effects on the analysis of some noisy and non-stationary signals, especially for the signal which contains the close frequency components. In this paper, an improved empirical wavelet transform is proposed. This method combines the advantages of piecewise cubic Hermite interpolating polynomial (PCHIP) and the EWT, and is named PCHIP-EWT. The main idea of the proposed method is to select useful sub-bands from the spectrum envelope. The proposed method selects the maximum points of the spectrum to reconstruct the spectrum envelope on the basis of PCHIP. Then, a new concept and a threshold named the Local Power (LP) and λ are defined. Based on the new concept LP and the λ, the useful sub-bands can be obtained. Finally, the experimental results demonstrate that the PCHIP-EWT is effective in analyzing noise and non-stationary signals, especially those that contain the closely-spaced frequencies.
科研通智能强力驱动
Strongly Powered by AbleSci AI