Nonpolynomial Spline Based Empirical Mode Decomposition

被引：0

作者：

Singh, Pushpendra ^{[1
]}

Srivastava, Pankaj Kumar ^{[2
]}

Patney, Rakesh Kumar ^{[1
]}

Joshi, Shiv Dutt ^{[1
]}

Saha, Kaushik ^{[3
]}

机构：

[1] Indian Inst Technol, Dept Elect Engn, Delhi, India

[2] Jaypee Inst Informat Technol, Dept Math, Noida, India

[3] STMicroelect India Pvt Ltd, Noida, India

来源：

2013 INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION (ICSC) | 2013年

关键词：

Empirical mode decomposition; mode mixing; non polynomial spline; intrinsic mode functions; detrend uncertainty; SOLVING DIFFERENTIAL-EQUATIONS; NUMERICAL-SOLUTION; COMPUTATIONAL TECHNIQUES; SYSTEM;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Authors propose a non polynomial spline based Empirical Mode Decomposition (EMD) algorithm to reduce mode mixing, and detrend uncertainty in analysis of time series. This new algorithm first locates original and pseudo extrema and then uses nonpolynomial spline interpolation to determine the upper and lower envelope at each decomposition step. A set of algebraic equations for the non polynomial spline interpolation is derived. A numerical simulation has been carried out for the analysis of error in spline interpolations. Various time series analysis have been preformed to show comparison among EMD and ensemble EMD (EEMD) based on polynomial spline, and non polynomial spline based EMD. Nonpolynomial spline based EMD algorithm is promising and generating better results.

引用

页码：435 / 440

页数：6

共 50 条

[11] Application of Empirical Mode Decomposition to Cardiorespiratory Synchronization
Wu, Ming-Chya
Hu, Chin-Kun
COMPLEX DYNAMICS IN PHYSIOLOGICAL SYSTEMS: FROM HEART TO BRAIN, 2009, : 167 - +
[12] B-SPLINE ANALYTICAL REPRESENTATION OF THE MEAN ENVELOPE FOR EMPIRICAL MODE DECOMPOSITION
Zheng, Tianxiang
Yang, Lihua
INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING, 2010, 8 (02) : 175 - 195
[13] Hierarchical decomposition based on a variation of empirical mode decomposition
Muhammad Kaleem
Aziz Guergachi
Sridhar Krishnan
Signal, Image and Video Processing, 2017, 11 : 793 - 800
[14] Hierarchical decomposition based on a variation of empirical mode decomposition
Kaleem, Muhammad
Guergachi, Aziz
Krishnan, Sridhar
SIGNAL IMAGE AND VIDEO PROCESSING, 2017, 11 (05) : 793 - 800
[15] Multivariate empirical mode decomposition
Rehman, N.
Mandic, D. P.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2010, 466 (2117): : 1291 - 1302
[16] Automated Diagnosis of Encephalopathy Based on Empirical Mode EEG Decomposition
J. E. Jacob
K. Gopakumar
T. Iype
A. Cherian
Neurophysiology, 2018, 50 : 278 - 285
[17] Electrocardiograph compression based on sifting process of empirical mode decomposition
Zhao, Chaojun
Chen, Zhijian
Meng, Jianyi
Xiang, Xiaoyan
ELECTRONICS LETTERS, 2016, 52 (09) : 688 - 689
[18] Automated Diagnosis of Encephalopathy Based on Empirical Mode EEG Decomposition
Jacob, J. E.
Gopakumar, K.
Iype, T.
Cherian, A.
NEUROPHYSIOLOGY, 2018, 50 (04) : 278 - 285
[19] Assessing the performance of rational spline-based empirical mode decomposition using a global annual precipitation dataset
Peel, M. C.
Mcmahon, T. A.
Pegram, G. G. S.
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2009, 465 (2106): : 1919 - 1937
[20] A power signal alteration analyzer based on empirical mode decomposition
Carni, Domenico Luca
Kermani, Mostafa
Lamonaca, Francesco
PROCEEDINGS OF 2022 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR LIVING ENVIRONMENT (IEEE METROLIVEN 2022), 2022, : 298 - 302

← 1 2 3 4 5 →