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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
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Multi – Linear in Multiple Nonparametric Regression , Detection and Treatment Using Simulation
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             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the

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Publication Date
Sun Sep 22 2019
Journal Name
Baghdad Science Journal
Geometry, and Normal Modes of Vibration (3N-6) for Di and Tetra-Rings Layer (6, 0) Linear (Zigzag) SWCNTs; A DFT Treatment
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            Density Functional Theory (DFT) method of the type (B3LYP) and a Gaussian basis set (6-311G) were applied for calculating the vibration frequencies and absorption intensities for normal coordinates (3N-6) at the equilibrium geometry of the Di and Tetra-rings layer (6, 0) zigzag single wall carbon nanotubes (SWCNTs) by using Gaussian-09 program. Both were found to have the same symmetry of D6d point group with C--C bond alternation in all tube rings (for axial bonds, which are the vertical C--Ca bonds in rings layer and for circumferential bonds C—Cc in the outer and mid rings bonds). Assignments of the modes of vibration IR active and inactive vibration frequ

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Some Estimator Methods of Linear Regression Model With Auto-Correlated Errors With Application Data for the Wheat in Iraq
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This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
Approximate Solution of Delay Differential Equations Using the Collocation Method Based on Bernstien Polynomials???? ???????? ????????? ????????? ????????? ???????? ?????????? ???????? ??? ??????? ???? ?????????
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In this paper a modified approach have been used to find the approximate solution of ordinary delay differential equations with constant delay using the collocation method based on Bernstien polynomials.

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Nurse Scheduling Problem Using Hybrid Simulated Annealing Algorithm
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Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Real-time Image Processing
Fast and efficient recursive algorithm of Meixner polynomials
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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Hexapod Robot Static Stability Enhancement using Genetic Algorithm
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Abstract

Hexapod robot is a flexible mechanical robot with six legs. It has the ability to walk over terrain. The hexapod robot look likes the insect so it has the same gaits. These gaits are tripod, wave and ripple gaits. Hexapod robot needs to stay statically stable at all the times during each gait in order not to fall with three or more legs continuously contacts with the ground. The safety static stability walking is called (the stability margin). In this paper, the forward and inverse kinematics are derived for each hexapod’s leg in order to simulate the hexapod robot model walking using MATLAB R2010a for all gaits and the geometry in order to derive the equations of the sub-constraint workspaces for each

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Optimum Median Filter Based on Crow Optimization Algorithm
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          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

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Publication Date
Sun Dec 01 2002
Journal Name
Iraqi Journal Of Physics
An edge detection algorithm matching visual contour perception
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For several applications, it is very important to have an edge detection technique matching human visual contour perception and less sensitive to noise. The edge detection algorithm describes in this paper based on the results obtained by Maximum a posteriori (MAP) and Maximum Entropy (ME) deblurring algorithms. The technique makes a trade-off between sharpening and smoothing the noisy image. One of the advantages of the described algorithm is less sensitive to noise than that given by Marr and Geuen techniques that considered to be the best edge detection algorithms in terms of matching human visual contour perception.

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