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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 البيانات وباستعمال خمسة دوال رابطة مختلفة مثل Gaussian وFrank وTawn وRotation Tawn وJoe وبخمسة أحجام مختلفة للعينات عند ثلاثة مستويات ارتباط موجبة، واعتمادًا على الحلول المتعددة، أظهرت النتائج أن تقدير دالة الكثافة الرابطة بطريقة المويجات عندما يكون مستوى الارتباط  كانت الرابطة Gaussian في المرتبة الأولى تليها الرابطةFrank واحتلت الرابطة Joe   المرتبة الأخيرة. اما في حالة الارتباطات المتوسطة والضعيفة   كانت الرابطة Tawn في المرتبة الأولى تليها الرابطة Rotation Tawn في حين جاءت Gaussian بالمرتبة الأخيرة. بالاعتماد على المعايير (Root Mean Square Error, Akiake Information Criteria, and Logarithm likelihood criteria) ، وتبين من خلال الرسم (Contour plot)  والشكل ثلاثي الابعاد (3D plot) لدوال الرابطة الحقيقية. فضلا عن اشكال التمهيد لكل منها باستخدام طريقة (ECDWT)، ويتضح من خلال الاشكال الدائرية ان توزيع مشاهدات الدالة الرابطة المقدرة بطريقة (ECDWT) كان دقيقا عند الاطراف بينما كان اقل دقة عند المركز لكل من الدوال Gaussian   وTawn.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
linear equivalence determination of key-stream sequence using Z-Transform
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the research ptesents a proposed method to compare or determine the linear equivalence of the key-stream from linear or nonlinear key-stream

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Publication Date
Thu Jan 01 2015
Journal Name
Applied And Computational Mathematics
Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
Speech Signal Compression Using Wavelet And Linear Predictive Coding
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A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of th

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Sat Oct 02 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
Using the wavelet analysis to estimate the nonparametric regression model in the presence of associated errors
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Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Solving the Hotdog Problem by Using the Joint Zero-order Finite Hankel - Elzaki Transform
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This paper is concerned with combining two different transforms to present a new joint transform FHET and its inverse transform IFHET. Also, the most important property of FHET was concluded and proved, which is called the finite Hankel – Elzaki transforms of the Bessel differential operator property, this property was discussed for two different boundary conditions, Dirichlet and Robin. Where the importance of this property is shown by solving axisymmetric partial differential equations and transitioning to an algebraic equation directly. Also, the joint Finite Hankel-Elzaki transform method was applied in solving a mathematical-physical problem, which is the Hotdog Problem. A steady state which does not depend on time was discussed f

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Solving Fractional Damped Burgers' Equation Approximately by Using The Sumudu Transform (ST) Method
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       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Solving Fractional Damped Burgers' Equation Approximately by Using The Sumudu Transform (ST) Method
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       In this work, the fractional damped Burger's equation (FDBE) formula    = 0,

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of Engineering
3-D Object Recognition using Multi-Wavelet and Neural Network
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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