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Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number of epoch, minimum number of neurons in the hybrid network, high accuracy in the output without oscillation response as well as useful model for a one step ahead prediction controller for the nonlinear CSTR system that is used in the MATLAB simulation.

 

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Publication Date
Tue Dec 01 2020
Journal Name
Iraqi Journal Of Physics
Comparative study of the linear and nonlinear optical properties for different Iraqi heavy and light crude oils
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Iraqi oil crudes have some of the physical and chemical characteristics that distinguish it from other types of oil crudes in the world. Some of these features such us molecular composition, rheological, viscosity and emulsions are studied carefully by researchers. In this work, a comparative study of the linear and the non-linear optical properties for typical heavy and light crude oils of Iraqi origin was studied utilizing Z-scan technique. The He -Ne laser of wavelength 632.8 nm had been used for this purpose. These samples were collected from Basra and Kut oil fields. The values of the non-linear refractive index (n2), non-linear absorption coefficient (β), and third-order electrical susceptibility (χ3) were e

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Fri Oct 01 2021
Monitoring and controlling the speed and direction of a DC motor through FPGA and comparison of FPGA for speed and performance optimization
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<span lang="EN-US">We are living in the 21<sup>st</sup> century, an era of acquiring necessity in one click. As we, all know that technology is continuously reviving to stay ahead of advancements taking place in this world of making things easier for mankind. Technology has been putting his part in introducing different projects as we have used the field programmable gate arrays (FPGAs) development board of low cost and programmable logic done by the new evolvable cyclone software is optimized for specific energy based on Altera Cyclone II (EP2C5T144) through which we can control the speed of any electronic device or any Motor Control IP product targeted for the fan and pump. Altera Cyclone FPGAs’ is a board thro

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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Wed Jun 01 2022
Journal Name
Analytical Methods In Environmental Chemistry Journal
Design a continuous microfluidic flow cell for turbidimetric-flow injection technology: A new approach for routine analysis of active pharmaceutical formulations
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Publication Date
Wed Feb 20 2019
Journal Name
Political Sciences Journal
Article Japan's social structure and useful Implications for Iraq
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The development of Japanese society passed through long historical stages and as a result of the bitter experience of Japan in the Second World War and its exhaustion, it was able to build a modern modern state after 1945. Japan is a country of culture, civilization, science and technology, a country that appreciates the value of solidarity work. And the role of active civil society. This is what makes us in Iraq stand and draw their experience in the advancement and development, especially that they also passed bitter political stages, Iraq today passes through the most historical periods of forestry through its historical heritage in terms of the existence of complex social problems, the US occupation of Iraq in 2003 highlighte

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Interdisciplinary Mathematics
Study on approximate analytical methods for nonlinear differential equations
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In this work, an analytical approximation solution is presented, as well as a comparison of the Variational Iteration Adomian Decomposition Method (VIADM) and the Modified Sumudu Transform Adomian Decomposition Method (M STADM), both of which are capable of solving nonlinear partial differential equations (NPDEs) such as nonhomogeneous Kertewege-de Vries (kdv) problems and the nonlinear Klein-Gordon. The results demonstrate the solution’s dependability and excellent accuracy.

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Publication Date
Fri Nov 01 2013
Journal Name
Al-nahrain Journal Of Science
Modified third order iterative method for solving nonlinear equations
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Many numerical approaches have been suggested to solve nonlinear problems. In this paper, we suggest a new two-step iterative method for solving nonlinear equations. This iterative method has cubic convergence. Several numerical examples to illustrate the efficiency of this method by Comparison with other similar methods is given.