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A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multi
dimensional data (such as images or solid with variable density) is proposed here. The
decomposition is based on the applications of ensemble empirical mode decomposition
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Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and s
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热图像增强使用二维经验模式分解结合相关向量机的旋转机械故障诊断
-Thermal image enhancement using bi-dimensional empirical mode decomposition in combination with relevance vector machine for rotating machinery fault diagnosis
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基于经验模态分解和独立成分分析去噪的特点, 提出了一种联合独立成分分析和经验模态分解的混沌信号降噪方法. 利用经验模态分解对混沌信号进行分解, 根据平移不变经验模态分解的思想构造多维输入向量, 通过所构造的多维输入向量和独立成分分析对混沌信号的各层内蕴模态函数进行自适应去噪处理-Based on empirical mode decomposition and independent component analysis denoising characteristics, we propose
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bi-dimensional empirical mode decomposition (BEMD) and
dual-channel PCNN is proposed in this paper.
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The HHT represents a time-dependent series in
a two-dimensional (2-D) time-frequency domain by extracting
instan eous frequency components within the signal through
an Empirical Mode Decomposition (EMD) process. The analytical
background of t
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Morphological operation-based bi-dimensional
empirical mode decomposition for automatic
background removal of fringe patterns
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