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Article
GUI Simulation for Movement of Human Arm Driven by EMG Signal

Authors: Abbas Hussien Miry --- Abduladhem A.Ali --- Mohammed Zeki Al-Faiz
Journal: Engineering and Technology Journal مجلة الهندسة والتكنولوجيا ISSN: 16816900 24120758 Year: 2011 Volume: 29 Issue: 8 Pages: 1597-1609
Publisher: University of Technology الجامعة التكنولوجية

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Abstract

This work presents a simulation methodology applied to a human arm. It isaimed to allow the human-assisting manipulators to perform complex movementbased on electromyography (EMG) signal for patient person in Virtual Reality(VR). This work achieves better classification with multiple parameters based KNearestNeighbor for different movements of a prosthetic arm. A K- NearestNeighbor (K-NN) rule is one of the simplest and the most important methods inpattern recognition. The method implements in the 3D space and uses theMATLAB Ver.2009a approach. This methodology can be used with differentrobots to test the behavior of system and the different motion


Article
STRUCTURE OPTIMIZATION OF ARTIFICIAL NEURAL NETWORKS USING SWARM INTELLIGENT
أمثلة هيكلية الشبكات العصبية الاصطناعية باستخدام الحشود الذكية

Author: Dr. HANAN A. R. AKKAR الدكتور حنان عبد الرضا عكار
Journal: Al-Qadisiyah Journal for Engineering Sciences مجلة القادسية للعلوم الهندسية ISSN: 19984456 Year: 2011 Volume: 4 Issue: 2 Pages: 101-111
Publisher: Al-Qadisiyah University جامعة القادسية

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Abstract

The structure is a very important aspect in neural network design, it is not only impossible to determine an optimal structure for a given problem, it is even impossible to prove that a given structure is optimal. In this paper, PSO (Particle Swarm Optimization) are used to construct best ANN (Artificial Neural Network) architectures, and find an optimal pattern of connections and weights to reduce structure complexity by minimizing the number of connection weights in a Feed Forward Artificial Neural Network (FFANN). They are called Particle Swarm Optimization-Neural Network systems (PSONN). PSONN systems are examined through theoretical analysis and computer simulation using MATLAB package. They are tested by several different examples, where the tests show that PSO a more efficient and automated search method can be used to find an optimal topology of ANN. The best and trained network with few numbers of iteration is provided using PSONN for finding an optimal structure. Finally, a simpler network, faster training with higher accuracy than full connected network is obtained by using PSONN for finding optimal connections and weights.

تم في هذا البحث استخدام افضلية الحشد الجزيئي(PSO) لبناء افضل هيكلية للشبكات العصبية عن طريق تقليل ربط الاوزان ل(FFANN) وتدريب الشبكة العصبية بنفس النظام المسمى(PSONN). الهيكلية في تصميم الشبكات العصبية من الامور المهمة وتعتبر من اهم المشاكل التي يعاني منها المصمم لذلك من المهم البحث عن افضل تصميم للشبكات العصبية. تم الاختبار باستخدام الطرق النظرية والتمثيل بواسطة حقيبة MATLAB. حيث تم الاختبار باستخدام عدة امثلة وجد من خلالها ان PSOكفوء بايجاد افضل تصميم من حيث تقليل التعقيد في الربط بين خلية عصبية واخرى مما سرع في عمل الشبكة ولم يؤثر على ادائها وفي نفس الوقت تدريب الشبكة العصبية باستخدام PSO مما حسن اداء الشبكات العصبية بشكل كبير.

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