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Differential Evolution algorithm for linear frequency modulation radar signal denoising
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Signal denoising is directly related to sample estimation of received signals, either by estimating the equation parameters for the target reflections or the surrounding noise and clutter accompanying the data of interest. Radar signals recorded using analogue or digital devices are not immune to noise. Random or white noise with no coherency is mainly produced in the form of random electrons, and caused by heat, environment, and stray circuitry loses. These factors influence the output signal voltage, thus creating detectable noise. Differential Evolution (DE) is an effectual, competent, and robust optimisation method used to solve different problems in the engineering and scientific domains, such as in signal processing. This paper looks at the feasibility of using the differential evolution algorithm to estimate the linear frequency modulation received signal parameters for radar signal denoising. The results gave high target recognition and showed feasibility to denoise received signals.

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Frequency Domain Analysis for Geometric Nonlinear Seismic Response of Tall Reinforced Concrete Buildings
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This paper aims to study the second-order geometric nonlinearity effects of P-Delta on the dynamic response of tall reinforced concrete buildings due to a wide range of earthquake ground motion forces, including minor earthquake up to moderate and strong earthquakes. The frequency domain dynamic analysis procedure was used for response assessment. Reinforced concrete building models with different heights up to 50 stories were analyzed. The finite element software ETABS (version 16.0.3) was used to analyze reinforced concrete building models.

The study reveals that the percentage increase in buildings' sway and drift due to P-Delta effects are nearly constant for specific building height irrespective of the seism

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Publication Date
Fri Jan 16 2026
Journal Name
F1000research
Update Quasi-Newton Algorithm for Training ANN
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The proposed design of neural network in this article is based on new accurate approach for training by unconstrained optimization, especially update quasi-Newton methods are perhaps the most popular general-purpose algorithms. A limited memory BFGS algorithm is presented for solving large-scale symmetric nonlinear equations, where a line search technique without derivative information is used. On each iteration, the updated approximations of Hessian matrix satisfy the quasi-Newton form, which traditionally served as the basis for quasi-Newton methods. On the basis of the quadratic model used in this article, we add a new update of quasi-Newton form. One innovative features of this form's is its ability to estimate the energy functio

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Publication Date
Sun Nov 01 2020
Journal Name
International Journal Of Nonlinear Analysis And Applications
Two Efficient Methods For Solving Non-linear Fourth-Order PDEs
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This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

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Scopus
Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
The Modified Quadrature Method for solving Volterra Linear Integral Equations
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In this paper the modified trapezoidal rule is presented for solving Volterra linear Integral Equations (V.I.E) of the second kind and we noticed that this procedure is effective in solving the equations. Two examples are given with their comparison tables to answer the validity of the procedure.

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Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Neuro-Self Tuning Adaptive Controller for Non-Linear Dynamical Systems
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In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Secure communications by chaotic carrier signal using Lorenz model
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In this paper, the generation of a chaotic carrier by Lorenz model
is theoretically studied. The encoding techniques has been used is
chaos masking of sinusoidal signal (massage), an optical chaotic
communications system for different receiver configurations is
evaluated. It is proved that chaotic carriers allow the successful
encoding and decoding of messages. Focusing on the effect of
changing the initial conditions of the states of our dynamical system
e.i changing the values (x, y, z, x1, y1, and z1).

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Publication Date
Sat Dec 01 2012
Journal Name
2012 Ieee-embs Conference On Biomedical Engineering And Sciences
Compatibility of mother wavelet functions with the electroencephalographic signal
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Publication Date
Fri Oct 01 2010
Journal Name
Journal
Frequency of genodermatoses among Iraqi patients
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AH Haider R, N Adil A, AW Makram M, AK Abdulkaleq S, 2010

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Publication Date
Tue Jul 04 2023
Journal Name
South Asian Research Journal Of Medical Sciences
Frequency of Intestinal Parasites in Baghdad
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Parasitic diseases including amoebiasis, blastocystosis, giardiasis, trichomoniasis, and schistosomiasis, are all globally wide spread with harmful consequences. The present study was carried out to provide information of the prevalence of these diseases in some regions of Baghdad. Objectives: to detect the prevalence of human pathogenic parasites in some regions of Baghdad in stool samples and urine samples, and to determine the most common age group affected. Methods: Data were collected from Al-Kindy Teaching Hospital and Medical City Teaching Hospital, in the lab of parasitology from November 2018 to May 2019. The present study included (400) sample, which were collected from patients at different ages of both genders, samples of the st

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