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Solving quaternion nonsymmetric algebraic Riccati equations through zeroing neural networks
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<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel HZNN model, called HZ-QNARE, is presented for solving the TQNARE. The model functions fairly well, as demonstrated by two simulation tests. Additionally, the results demonstrated that, while both approaches function remarkably well, the HZNN architecture works better than the ZNN architecture.</p></abstract>

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Numerical Approach of Linear Volterra Integro-Differential Equations Using Generalized Spline Functions
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This paper is dealing with non-polynomial spline functions "generalized spline" to find the approximate solution of linear Volterra integro-differential equations of the second kind and extension of this work to solve system of linear Volterra integro-differential equations. The performance of generalized spline functions are illustrated in test examples

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Publication Date
Thu May 30 2024
Journal Name
Journal Of Interdisciplinary Mathematics
Analytical approximate solutions of random integro differential equations with laplace decomposition method
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An efficient combination of Adomian Decomposition iterative technique coupled with Laplace transformation to solve non-linear Random Integro differential equation (NRIDE) is introduced in a novel way to get an accurate analytical solution. This technique is an elegant combination of theLaplace transform, and the Adomian polynomial. The suggested method will convert differential equations into iterative algebraic equations, thus reducing processing and analytical work. The technique solves the problem of calculating the Adomian polynomials. The method’s efficiency was investigated using some numerical instances, and the findings demonstrate that it is easier to use than many other numerical procedures. It has also been established that (LT

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Scopus
Publication Date
Tue Feb 24 2026
Journal Name
Baghdad Science Journal
Oscillation Conditions for Solutions of First Order Piecewise Constant Neutral Differential Equations
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
CUSTOM ANALYSIS THROUGH Nth ORDER GAUSSIAN NOISE
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Publication Date
Thu Jan 01 2009
Journal Name
Iraqi Journal Of Physics
Resonance Tunneling Through GaN/AlGaN Superlattice System
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The purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε  VO.

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Publication Date
Sat Oct 01 2022
Journal Name
Al–bahith Al–a'alami
COMMUNICATION SKILLS THROUGH THE LANGUAGE OF SPEECH
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Language is the realistic and sensitive basis for any communication between two or more parties. It is an important workshop that prepares meanings and coding them according to a linguistic structure governed by agreed rules that speak to and coexist with everyone.

Whereas the forms of communication are: personal, mediator and mass, none of them can move away from language in their dealings and communication patterns. Since each has its own characteristics and skills, it must be launched in its fields through verbal and non-verbal symbols and wears the elements of influential language as intended.

It makes the recipient face two things: whether he fails to understand those symbols hence its purpose fail, or he meditates s

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Crossref
Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Physics
Resonance Tunneling Through GaN/AlGaN Superlattice System
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The purpose of our work is to report a theoretical study of electrons tunneling through semiconductor superlattice (SSL). The (SSL) that we have considered is (GaN/AlGaN) system within the energy range of ε < Vo, ε = Vo and ε > Vo, where Vo is the potential barrier height. The transmission coefficient (TN) was determined using the transfer matrix method. The resonant energies are obtained from the T (E) relation. From such system, we obtained two allowed quasi-levels energy bands for ε < VO and one band for ε  VO.

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Crossref
Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Intelligent Systems And Internet Of Things
Enhancing Convolutional Neural Network for Image Retrieval
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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