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Algorithms for Computing of Optimization Problems with a Common Minimum-Norm Fixed Point with Applications

Year: 2016 Volume: 10 Issue: 12 688 - 696 Pages

• Authors:
• Apirak Sombat
• Teerapol Saleewong
• Poom Kumam
• Parin Chaipunya
• Wiyada Kumam
• Anantachai Padcharoen
• Yeol Je Cho
• Thana Sutthibutpong

Abstract: This research is aimed to study a two-step iteration process defined over a finite family of σ-asymptotically quasi-nonexpansive nonself-mappings. The strong convergence is guaranteed under the framework of Banach spaces with some additional structural properties including strict and uniform convexity, reflexivity, and smoothness assumptions. With similar projection technique for nonself-mapping in Hilbert spaces, we hereby use the generalized projection to construct a point within the corresponding domain. Moreover, we have to introduce the use of duality mapping and its inverse to overcome the unavailability of duality representation that is exploit by Hilbert space theorists. We then apply our results for σ-asymptotically quasi-nonexpansive nonself-mappings to solve for ideal efficiency of vector optimization problems composed of finitely many objective functions. We also showed that the obtained solution from our process is the closest to the origin. Moreover, we also give an illustrative numerical example to support our results.

• Keywords:
• σ-asymptotically quasi-nonexpansive nonselfmapping
• strong convergence
• fixed point
• uniformly convex and uniformly smooth Banach space.

Level Set and Morphological Operation Techniques in Application of Dental Image Segmentation

Year: 2014 Volume: 8 Issue: 4 187 - 190 Pages

• Authors:
• Abdolvahab Ehsani Rad
• Mohd Shafry Mohd Rahim
• Alireza Norouzi

Abstract: Medical image analysis is one of the great effects of computer image processing. There are several processes to analysis the medical images which the segmentation process is one of the challenging and most important step. In this paper the segmentation method proposed in order to segment the dental radiograph images. Thresholding method has been applied to simplify the images and to morphologically open binary image technique performed to eliminate the unnecessary regions on images. Furthermore, horizontal and vertical integral projection techniques used to extract the each individual tooth from radiograph images. Segmentation process has been done by applying the level set method on each extracted images. Nevertheless, the experiments results by 90% accuracy demonstrate that proposed method achieves high accuracy and promising result.

• Keywords:
• Integral production
• level set method
• morphological operation
• segmentation.

Restarted Generalized Second-Order Krylov Subspace Methods for Solving Quadratic Eigenvalue Problems

Year: 2010 Volume: 4 Issue: 7 944 - 951 Pages

• Authors:
• Liping Zhou
• Liang Bao
• Yiqin Lin
• Yimin Wei
• Qinghua Wu

Abstract: This article is devoted to the numerical solution of large-scale quadratic eigenvalue problems. Such problems arise in a wide variety of applications, such as the dynamic analysis of structural mechanical systems, acoustic systems, fluid mechanics, and signal processing. We first introduce a generalized second-order Krylov subspace based on a pair of square matrices and two initial vectors and present a generalized second-order Arnoldi process for constructing an orthonormal basis of the generalized second-order Krylov subspace. Then, by using the projection technique and the refined projection technique, we propose a restarted generalized second-order Arnoldi method and a restarted refined generalized second-order Arnoldi method for computing some eigenpairs of largescale quadratic eigenvalue problems. Some theoretical results are also presented. Some numerical examples are presented to illustrate the effectiveness of the proposed methods.

• Keywords:
• Quadratic eigenvalue problem
• Generalized secondorder Krylov subspace
• Generalized second-order Arnoldi process
• Projection technique
• Refined technique
• Restarting.

Swarmed Discriminant Analysis for Multifunction Prosthesis Control

Year: 2011 Volume: 5 Issue: 3 116 - 123 Pages

• Authors:
• Rami N. Khushaba
• Ahmed Al-Ani
• Adel Al-Jumaily

Abstract: One of the approaches enabling people with amputated limbs to establish some sort of interface with the real world includes the utilization of the myoelectric signal (MES) from the remaining muscles of those limbs. The MES can be used as a control input to a multifunction prosthetic device. In this control scheme, known as the myoelectric control, a pattern recognition approach is usually utilized to discriminate between the MES signals that belong to different classes of the forearm movements. Since the MES is recorded using multiple channels, the feature vector size can become very large. In order to reduce the computational cost and enhance the generalization capability of the classifier, a dimensionality reduction method is needed to identify an informative yet moderate size feature set. This paper proposes a new fuzzy version of the well known Fisher-s Linear Discriminant Analysis (LDA) feature projection technique. Furthermore, based on the fact that certain muscles might contribute more to the discrimination process, a novel feature weighting scheme is also presented by employing Particle Swarm Optimization (PSO) for estimating the weight of each feature. The new method, called PSOFLDA, is tested on real MES datasets and compared with other techniques to prove its superiority.

• Keywords:
• Discriminant Analysis
• Pattern Recognition
• SignalProcessing.