ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.
In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
Although the Wiener filtering is the optimal tradeoff of inverse filtering and noise smoothing, in the case when the blurring filter is singular, the Wiener filtering actually amplify the noise. This suggests that a denoising step is needed to remove the amplified noise .Wavelet-based denoising scheme provides a natural technique for this purpose .
In this paper a new image restoration scheme is proposed, the scheme contains two separate steps : Fourier-domain inverse filtering and wavelet-domain image denoising. The first stage is Wiener filtering of the input image , the filtered image is inputted to adaptive threshold wavelet
... Show MoreIn this research local wheat peel was used as an adsorbent surface for removal of Azure B (AB) dye from the aqueous solution. The adsorption process was performed at different experimental parameters, equilibrium time, temperature, ionic strength and solution pH. The isotherms of adsorption are of H-type as compared with Giles curves and the adsorption data were coincide with Freundlich equation. The adsorption kinetic data were analyzed using pseudo- first and second order kinetic models. The effect of temperature was studied and the amount of dye adsorbed was found to increase with the increasing of temperature from 25 to 50 oC. The values of thermodynamic functions like enthalpy and entropy have been estimated. The quantity of adso
... Show More?Natural Occurrence of aflatoxin Bi and B2 was investigated monthly in paddy rice stored for duration of six months. Aflatoxin B| was detected at the beginning of storage. The concentration of aflatoxin Bi in paddy and polished rice was found to be (0.3 and ()) ppb respectively while aflatoxin B2 W'as not detected in both paddy and polished rice afler six months of storage, concentration of aflatoxin Bi ‘ ’ ' reached 3 ppb in paddy rice and 0.9 ppb in polished rice, while the study proved that the concentration of aflatoxin in paddy rice was higher than polished rice as a result of processing which reduce the toxin
Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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