• Journal of applied mathematics & informatics
• /
• 제26권1_2호
• /
• pp.251-261
• /
• 2008

In this paper second order cone convex, second order cone pseudoconvex, second order strongly cone pseudoconvex and second order cone quasiconvex functions are introduced and their interrelations are discussed. Further a MondWeir Type second order dual is associated with the Vector Minimization Problem and the weak and strong duality theorems are established under these new generalized convexity assumptions.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
• /
• pp.502-505
• /
• 2004

An intelligent digital redesign technique (IDR) for the observer-based output feedback Takagi-Sugeno (T-S) fuzzy control system with unmeasurable premise variables is developed. The considered IDR condition is cubically parameterized as convex minimization problems of the norm distances between linear operators to be matched.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2002년도 ICCAS
• /
• pp.64.5-64
• /
• 2002

This paper concerns a new digital redesign (DR) technique for an observer-based output-feedback control (OBOFC) system. The term DR involves converting an analog controller into an equivalent digital one in the sense of state-matching. The considered DR problem is formulated as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separation principle on the DR of the OBOFC is explicitly shown. A numerical example is included for visualizing the feasibility of the proposed technique.

• Journal of applied mathematics & informatics
• /
• 제24권1_2호
• /
• pp.333-342
• /
• 2007

A nonsmooth PGD scheme for minimizing a nonsmooth convex function is presented. In the parallelization step of the algorithm, a method due to Pang, Han and Pangaraj (1991), [7], is employed to solve a subproblem for constructing search directions. The convergence analysis is given as well.

• Journal of applied mathematics & informatics
• /
• 제23권1_2호
• /
• pp.311-319
• /
• 2007

This article studies a modified BFGS algorithm for solving smooth unconstrained strongly convex minimization problem. The modified BFGS method is based on the new quasi-Newton equation $B_k+1{^s}_k=yk\;where\;y_k^*=yk+A_ks_k\;and\;A_k$ is a matrix. Wei, Li and Qi [WLQ] have proven that the average performance of two of those algorithms is better than that of the classical one. In this paper, we prove the global convergence of these algorithms associated to a general line search rule.

• 대한의용생체공학회:의공학회지
• /
• 제35권5호
• /
• pp.151-159
• /
• 2014

Computed tomography (CT) is one of the most widely used medical imaging modality. However, substantial x-ray dose exposed to the human subject during the CT scan is a great concern. Region-of-interest (ROI) CT is considered to be a possible solution for its potential to reduce the x-ray dose to the human subject. In most of ROI-CT scans, the ROI is set to a circular shape whose diameter is often considerably smaller than the full field-of-view (FOV). However, an arbitrarily shaped ROI is very desirable to reduce the x-ray dose more than the circularly shaped ROI can do. We propose a new method to make a non-circular convex-shaped ROI along with the image reconstruction method. To make a ROI with an arbitrary convex shape, dynamic collimations are necessary to minimize the x-ray dose at each angle of view. In addition to the dynamic collimation, we get the ROI projection data with slightly lower sampling rate in the view direction to further reduce the x-ray dose. We reconstruct images from the ROI projection data in the compressed sensing (CS) framework assisted by the exterior projection data acquired from the pilot scan to set the ROI. To validate the proposed method, we used the experimental micro-CT projection data after truncating them to simulate the dynamic collimation. The reconstructed ROI images showed little errors as compared to the images reconstructed from the full-FOV scan data as well as little artifacts inside the ROI. We expect the proposed method can significantly reduce the x-ray dose in CT scans if the dynamic collimation is realized in real CT machines.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권8호
• /
• pp.2722-2742
• /
• 2014

We propose methods of linear transceiver design for two different power constraints, sum relay power constraint and per relay power constraint, which determine signal processing matrices such as base station (BS) transmitter, relay precoders and user receivers to minimize sum mean square error (SMSE) for multi-relay multi-user (MRMU) networks. However, since the formulated problem is non-convex one which is hard to be solved, we suboptimally solve the problems by defining convex subproblems with some fixed variables. We adopt iterative sequential designs of which each iteration stage corresponds to each subproblem. Karush-Kuhn-Tucker (KKT) theorem and SMSE duality are employed as specific methods to solve subproblems. The numerical results verify that the proposed methods provide comparable performance to that of a full relay cooperation bound (FRCB) method while outperforming the simple amplify-and-forward (SAF) and minimum mean square error (MMSE) relaying in terms of not only SMSE, but also the sum rate.

• Journal of Electrical Engineering and Technology
• /
• 제10권5호
• /
• pp.1940-1949
• /
• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권12호
• /
• pp.5614-5633
• /
• 2018

Mobile Edge Computing (MEC) and Wireless Power Transfer (WPT) are both recognized as promising techniques, one is for solving the resource insufficient of mobile devices and the other is for powering the mobile device. Naturally, by integrating the two techniques, task will be capable of being executed by the harvested energy which makes it possible that less intrinsic energy consumption for task execution. However, this innovative integration is facing several challenges inevitably. In this paper, we aim at prolonging the battery life of mobile device for which we need to maximize the harvested energy and minimize the consumed energy simultaneously, which is formulated as residual energy maximization (REM) problem where the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device are all considered as key factors. To this end, we jointly optimize the offloading ratio, energy harvesting time, CPU frequency and transmission power of mobile device to solve the REM problem. Furthermore, we propose an efficient convex optimization and sequential unconstrained minimization technique based combining method to solve the formulated multi-constrained nonlinear optimization problem. The result shows that our joint optimization outperforms the single optimization on REM problem. Besides, the proposed algorithm is more efficiency.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
• /
• pp.199-202
• /
• 2002

This parer concerns a design methodology of the observer-based output-feedback digital controller for Takagj-Sugeno (TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.