Preferred Language
Articles
/
GhdIU44BVTCNdQwCfEIj
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
...Show More Authors

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it is obvious that the number of moments selected by the SP should exceed 30% of the overall EEG samples for accuracy to be over 90%.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Jan 01 2013
Journal Name
Brain Research Bulletin
A note on the probability distribution function of the surface electromyogram signal
...Show More Authors

View Publication
Scopus (78)
Crossref (80)
Scopus Clarivate Crossref
Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
...Show More Authors
Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
View Publication
Scopus (3)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
...Show More Authors

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Evaluation of Textile Filter in Field Drains
...Show More Authors

The role of drain in agricultural lands is to remove excess surface and subsurface water to create a good environment for root growth and to increase crops yield. The main objective of this research was to evaluate the performance of closed drains when using textile filter instead of crushed gravel filter. The research has been executed in the laboratory using a sand tank model and by using two types of the soil. One of soils was light soil (sandy soil) and the other heavy soil (loamy soil). The tests were classified into four cases; each case was supplied discharge during 10 days. The results showed that the amount of out flow when using graded crushed gravel filter is greater than the amount of out flow in case of usin

... Show More
View Publication Preview PDF
Publication Date
Mon Jan 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
ON-Line MRI Image Selection and Tumor Classification using Artificial Neural Network
...Show More Authors

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Feb 10 2019
Journal Name
Iraqi Journal Of Physics
A nonlinear edge –preserving smoothing filter for edge detection on color and gray satellite images
...Show More Authors

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.

View Publication Preview PDF
Crossref
Publication Date
Sun Sep 11 2022
Journal Name
Concurrency And Computation: Practice And Experience
Fast and accurate computation of high‐order Tchebichef polynomials
...Show More Authors

View Publication
Scopus (25)
Crossref (23)
Scopus Clarivate Crossref
Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Forecasting enhancement using a hodrick-prescott filter
...Show More Authors

: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

... Show More
Preview PDF
Scopus
Publication Date
Fri May 01 2020
Journal Name
Journal Of Engineering
Semi-Analytical Prediction of Flank Tool Wear in Orthogonal Cutting of Aluminum
...Show More Authors

This study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.

View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Orthogonal Functions Solving Linear functional Differential EquationsUsing Chebyshev Polynomial
...Show More Authors

A method for Approximated evaluation of linear functional differential equations is described. where a function approximation as a linear combination of a set of orthogonal basis functions which are chebyshev functions .The coefficients of the approximation are determined by (least square and Galerkin’s) methods. The property of chebyshev polynomials leads to good results , which are demonstrated with examples.

View Publication Preview PDF
Crossref (3)
Crossref