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Perturbation iteration transform method for solving fractional order integro-differential equation
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Publication Date
Wed Jun 01 2022
Journal Name
V. International Scientific Congress Of Pure, Applied And Technological Sciences
Lightweight Image Compression Using Polynomial and Transform Coding
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Publication Date
Tue Sep 27 2022
Journal Name
Journal Of Engineering Research And Sciences
Images Compression using Combined Scheme of Transform Coding
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Some problems want to be solved in image compression to make the process workable and more efficient. Much work had been done in the field of lossy image compression based on wavelet and Discrete Cosine Transform (DCT). In this paper, an efficient image compression scheme is proposed, based on a common encoding transform scheme; It consists of the following steps: 1) bi-orthogonal (tab 9/7) wavelet transform to split the image data into sub-bands, 2) DCT to de-correlate the data, 3) the combined transform stage's output is subjected to scalar quantization before being mapped to positive, 4) and LZW encoding to produce the compressed data. The peak signal-to-noise (PSNR), compression ratio (CR), and compression gain (CG) measures were used t

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Publication Date
Fri Nov 01 2024
Journal Name
Baghdad Science Journal
Estimation of Copula Density Using the Wavelet Transform
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يقترح هذا البحث طريقة جديدة لتقدير دالة كثافة الرابطة باستخدام تحليل المويجات كطريقة لامعلمية، من أجل الحصول على نتائج أكثر دقة وخالية من مشكلة تاثيرات الحدود التي تعاني منها طرائق التقدير اللامعلمية. اذ تعد طريقة المويجات طريقة اوتماتيكية للتعامل مع تاثيرات الحدود وذلك لانها لا تأخذ بنظر الاعتبار إذا كانت السلسلة الزمنية مستقرة او غير مستقرة. ولتقدير دالة كثافة الرابطة تم استعمال المحاكاة لتوليد البي

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Publication Date
Sun Jul 01 2018
Journal Name
International Journal Of Engineering Research And Management
The first and Second Order Polynomial Models with Double Scalar Quantization for Image Compression
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Publication Date
Mon Jan 01 2024
Journal Name
Applied And Computational Mathematics
Reliable computational methods for solving Jeffery-Hamel flow problem based on polynomial function spaces
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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
High Order Sliding Mode Observer-Based Output Feedback Controller Design For Electro-Hydraulic System
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A perturbed linear system with property of strong observability ensures that there is a sliding mode observer to estimate the unknown form inputs together with states estimation. In the case of the electro-hydraulic system with piston position measured output, the above property is not met. In this paper, the output and its derivatives estimation were used to build a dynamic structure that satisfy the condition of strongly observable. A high order sliding mode observer (HOSMO) was used to estimate both the resulting unknown perturbation term and the output derivatives. Thereafter with one signal from the whole system (piton position), the piston position make tracking to desire one with a simple linear output feedback controller after ca

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Deriving the Composite Simpson Rule by Using Bernstein Polynomials for Solving Volterra Integral Equations
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In this paper we use Bernstein polynomials for deriving the modified Simpson's 3/8 , and the composite modified Simpson's 3/8 to solve one dimensional linear Volterra integral equations of the second kind , and we find that the solution computed by this procedure is very close to exact solution.

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Publication Date
Wed Sep 05 2007
Journal Name
Neural Network World
A canonical generic algorithm for likelihood estimator of first order moving average model parameter
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The increasing availability of computing power in the past two decades has been use to develop new techniques for optimizing solution of estimation problem. Today's computational capacity and the widespread availability of computers have enabled development of new generation of intelligent computing techniques, such as our interest algorithm, this paper presents one of new class of stochastic search algorithm (known as Canonical Genetic' Algorithm ‘CGA’) for optimizing the maximum likelihood function strategy is composed of three main steps: recombination, mutation, and selection. The experimental design is based on simulating the CGA with different values of are compared with those of moment method. Based on MSE value obtained from bot

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Scopus (3)
Scopus
Publication Date
Sat Nov 01 2014
Journal Name
I-manager's Journal On Information Technology
AN ENHANCED METHOD FOR SPRITE EXTRACTING
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The extracting of personal sprite from the whole image faced many problems in separating the sprite edge from the unneeded parts, some image software try to automate this process, but usually they couldn't find the edge or have false result. In this paper, the authors have made an enhancement on the use of Canny edge detection to locate the sprite from the whole image by adding some enhancement steps by using MATLAB. Moreover, remove all the non-relevant information from the image by selecting only the sprite and place it in a transparent background. The results of comparing the Canny edge detection with the proposed method shows improvement in the edge detection.