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EMD2FNN: A strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction
Stock market forecasting is a vital component of financial systems. However, the stock prices
are highly noisy and non-stationary due to the fact that stock markets are affected by a …
are highly noisy and non-stationary due to the fact that stock markets are affected by a …
Texture analysis based on local analysis of the bidimensional empirical mode decomposition
The main contribution of our approach is to apply the Hilbert-Huang Transform (which
consists of two parts:(a) Empirical Mode Decomposition (EMD), and (b) the Hilbert spectral …
consists of two parts:(a) Empirical Mode Decomposition (EMD), and (b) the Hilbert spectral …
Two-dimensional empirical mode decomposition by finite elements
Empirical mode decomposition (EMD) is a powerful tool for analysis of non-stationary and
nonlinear signals, and has drawn significant attention in various engineering application …
nonlinear signals, and has drawn significant attention in various engineering application …
Detection of image splicing based on Hilbert-Huang transform and moments of characteristic functions with wavelet decomposition
Image splicing is a commonly used technique in image tampering. This paper presents a
novel approach to passive detection of image splicing. In the proposed scheme, the image …
novel approach to passive detection of image splicing. In the proposed scheme, the image …
SAR and multispectral image fusion using generalized IHS transform based on à trous wavelet and EMD decompositions
In the intensity hue saturation (IHS) based image fusion, the enhancement of the spatial
information often leads to the distortion of the information in the spectral domain. In this …
information often leads to the distortion of the information in the spectral domain. In this …
[PDF][PDF] Image fusion and enhancement via empirical mode decomposition
In this paper, we describe a novel technique for image fusion and enhancement, using
Empirical Mode Decomposition (EMD). EMD is a non-parametric data-driven analysis tool …
Empirical Mode Decomposition (EMD). EMD is a non-parametric data-driven analysis tool …
Empirical mode decomposition: Applications on signal and image processing
In this paper, we propose some recent works on data analysis and synthesis based on
Empirical Mode Decomposition (EMD). Firstly, a direct 2D extension of original Huang EMD …
Empirical Mode Decomposition (EMD). Firstly, a direct 2D extension of original Huang EMD …
Fusion of visible and infrared images using empirical mode decomposition to improve face recognition
In this effort, we propose a new image fusion technique, utilizing empirical mode
decomposition (EMD), for improved face recognition. EMD is a non-parametric data-driven …
decomposition (EMD), for improved face recognition. EMD is a non-parametric data-driven …
Improved bi-dimensional EMD and Hilbert spectrum for the analysis of textures
X Guanlei, W **aotong, X **aogang - Pattern Recognition, 2009 - Elsevier
An improved bi-dimensional empirical mode decomposition (IBEMD) is proposed. Structure
of image extremas represents the important feature of images, and is useful for the …
of image extremas represents the important feature of images, and is useful for the …
Fusing remote sensing images using à trous wavelet transform and empirical mode decomposition
À trous wavelet transform (AWT) and empirical mode decomposition (EMD) are two distinct
methods used for analyzing nonlinear and nonstationary signals. In this paper, a …
methods used for analyzing nonlinear and nonstationary signals. In this paper, a …