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.
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
... Show MoreIn 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
... Show MoreThe follower of the art of Arabic calligraphy accurately identifies three prominent dimensions that have framed the dimensions of this art, the functional dimension and the aesthetic dimension, the last of which is the expressive dimension, as it is an art that does not exhaust its aesthetic and indicative purposes because of its possibilities and characteristics that help it to form with any entity designed by calligrapher, with the expressive dimension of the most important of those The dimensions that can be studied within multiple variables, the most important of which are the significance of the text, the spatial and formal organization of the calligraphic functions and the power of the idea from which the calligraphic formation eme
... Show MoreAH Haider R, N Adil A, AW Makram M, AK Abdulkaleq S, 2010
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
... Show MoreThis paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni
... Show MoreHR Al-Hamami, AA Noaimi, MM Al-Waiz, AS Al-Kabraty, Iraqi Postgraduate Medical Journal, 2010 - Cited by 4
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).
Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh
... Show More