A novel algorithm for 2D object orientation and scaling factor estimation, is proposed in this paper. The proposed method is accurate, effective, computationally efficient and fullyautomated. The object orientation is calculated by using object principal axes estimation. The main contribution of the proposed approach is the utilization of a 2D empirical mode like decomposition (EMD-like) as a n...

The forecasting of tourist arrival depends on the accurate modeling prevalent data patterns found in arrival, especially for daily where changes are more complex and highly nonlinear. In this paper, a new multiscale mode learning-based model is proposed to exploit different features movement. Two popular Mode Decomposition models (MD) Convolutional Neural Network (CNN) introduced at scales extr...

Identifying key elements of the ECG signal in modern day's diagnostic devices is crucial. Making a preliminary assessment of a patient during emergency situations, i.e. before arriving to the hospital, is starting to be a generally accepted practice in more and more countries. This article proposes a possible method of differentiating the T-wave from other features of the ECG signal based on th...

A new method to detect coal gangue interface by utilizing vibration signal of coal and gangue is presented for coal and gangue interface detection on fully mechanized mining face. Because of non-stationary characteristics contained in response signals under complicated environment, empirical mode decomposition algorithm was used to decompose the original vibration signal into the intrinsic mode...

Abstract. Empirical Mode Decomposition (EMD) is widely used in biomedical field for biomedical signal processing and especially for electrocardiogram (ECG) processing. Removal of artifacts that corrupt ECG, is carried out by proper selection of Intrinsic Mode Functions (IMF) for the partial signal reconstruction. In this paper a study of the influence of White Gaussian Noise in synthetic electr...

This paper considers an improvement of empirical mode decomposition (EMD) in the presence of missing data. EMD has been widely used to decompose nonlinear and nonstationary signals into some components according to intrinsic frequency called intrinsic mode functions. However, the conventional EMD may not be efficient when missing values are present. This paper proposes a modified EMD procedure ...

Abstract—This paper presents a denoising method called EMDCustom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to imp...

An extracellular signaling molecule acts on several types of cells, evoking characteristic and different responses depending on intrinsic factors in the signal-receiving cells. In ascidian embryos, notochord and mesenchyme are induced in the anterior and posterior margins, respectively, of the vegetal hemisphere by the same FGF signal emanating from endoderm precursors. The difference in the re...

This work proposes a neural-fuzzy sliding mode control scheme for a hydro-turbine speed governor system. Considering the assumption of elastic water hammer, a nonlinear mode of the hydro-turbine governor system is established. By linearizing this mode, a sliding mode controller is designed. The linearized mode is subject to uncertainties. The uncertainties are generated in the process of linear...