摘要
经验模态分解是希尔伯特-黄变换分析的核心,是有效计算瞬时频率的必要前提条件。该文介绍经验模态分解的算法,并在传统小波阈值去噪法的基础上提出了一种基于经验模态分解的去噪法,进而提高分解的准确性和时效性,使希尔伯特-黄变换在信号的分析中更具实用性。试验结果证明,基于经验模态分解的去噪效果是相当有效和稳定的,为后续希尔伯特变换提供稳定的依据。
EMD is the core of hilbert-huang transform(HHT) analysis,and is the necessary prerequisite.The paper introduces EMD algorithm.It is proposed EMD threshold denoising method based on traditional wavelet threshold denoising method so as to improve the accuracy and timeliness of decomposition EMD,make EMD algorithm in signal analysis is more practical.The test results show that based on emd de-noising result is quite effective and stable,for follow-up Hilbert transformation to provide a stable basis.
作者
张翀
ZHANG Chong (Taiyuan Senior School of Technicians,Taiyuan 030021,China)
出处
《电脑知识与技术（过刊）》
2010年第35期10113-10115,共3页
Computer Knowledge and Technology
关键词
希尔伯特变换
经验模态分解
噪声
阈值
hilbert-huang transform
empirical mode decomposition
noise
threshold
