• Title/Summary/Keyword: linear algorithm

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An Linear Bottleneck Assignment Problem (LBAP) Algorithm Using the Improving Method of Solution for Linear Minsum Assignment Problem (LSAP)

  • Lee, Sang-Un
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.1
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    • pp.131-138
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    • 2016
  • In this paper, we propose a simple linear bottleneck assignment problems (LBAP) algorithm to find the optimal solution. Generally, the LBAP has been solved by threshold or augmenting path algorithm. The primary characteristic of proposed algorithm is derived the optimal solution of LBAP from linear sum assignment problem (LSAP). Firstly, we obtains the solution for LSAP from the selected minimum cost of rows and moves the duplicated costs in row to unselected row with minimum increasing cost in direct and indirect paths. Then, we obtain the optimal solution of LBAP according to the maximum cost of LSAP can be move to less cost. For the 29 balanced and 7 unbalanced problem, this algorithm finds optimal solution as simple.

Efficient Alalysis of Resistive Networks With Canonical Piecewise-Linear Equations (정규 구간선형 방정식을 갖는 저항성 회로의 효율적인 해석)

  • 조준영;조진국;권용세;김영환
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.12
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    • pp.142-151
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    • 1994
  • This paper proposes new algorithms to solve canonical piecewise-linear equations with linear partitions and illustrates their efficiency through the analysis of resistive network. The basic idea of the proposed algorithm is to find the best next guess, closest to the actual solution, at each Newton-Raphson (N-R) iteration by comparing the images of nest guess candidates and that of the actual solution. The proposed algorithm can reduce the number of the N-R iterations rquired for convergence greatly, compared to the actual solution, at each Newton-Raphson (N-R) iteration by comparing the images of next guess candidates and that of the actual solution. The proposed algorithm can reduce the number of the N-R iterations required for convergence greatly, compared to the Katzenelson algorithm. When applied to analyzing test circuits, the proposed algorithm required 8 to 20 times fewer N-R iterations and 5 to 10 times less CPU time than the Katzenelson algorithm, depending on the size of the circuits. The experimental results also exhibit that the efficiency of the proposed algorithm over the Katzenelson algorithm increases as the number of the piecewise-linear regions for the representation of the circuit.

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Virtual Network Mapping Algorithm for Minimizing Piecewise Linear Cost Function (Piecewise Linear 비용함수의 최소화를 위한 가상 네트워크 매핑 알고리즘)

  • Pyoung, Chan-kyu;Baek, Seung-jun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.6
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    • pp.672-677
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    • 2016
  • Development of Internet has been successfully inspired with extensive deployment of the network technology and application. However, increases in Internet usage had caused a lot of traffic overload in these days. Thus, we need a continuous research and development on the network virtualization for effective resource allocation. In this paper, we propose a minimal cost virtual network mapping algorithm using Piecewise Linear Cost Function. We exploited an algorithm with Linear Programming and D-VINE for node mapping, and Shortest Path Algorithm based on linear programming solution is used for link mapping. In this way, we compared and analyzed the average cost for arrival rate of VN request with linear and tree structure. Simulation results show that the average cost of our algorithm shows better efficiency than ViNEyard.

Adaptive control of rotationally non-linear asymmetric structures under seismic loads

  • Amini, Fereidoun;Rezazadeh, Hassan;Afshar, Majid Amin
    • Structural Engineering and Mechanics
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    • v.65 no.6
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    • pp.721-730
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    • 2018
  • This paper aims to inspect the effectiveness of the Simple Adaptive Control Method (SACM) to control the response of asymmetric buildings with rotationally non-linear behavior under seismic loads. SACM is a direct control method and was previously used to improve the performance of linear and non-linear structures. In most of these studies, the modeled structures were two-dimensional shear buildings. In reality, the building plans might be asymmetric, which cause the buildings to experience torsional motions under earthquake excitation. In this study, SACM is used to improve the performance of asymmetric buildings, and unlike conventional linear models, the non-linear inertial coupling terms are considered in the equations of motion. SACM performance is compared with the Linear Quadratic Regulator (LQR) algorithm. Moreover, the LQR algorithm is modified, so that it is appropriate for rotationally non-linear buildings. Active tuned mass dampers are used to improve the performance of the modeled buildings. The results show that SACM is successful in reducing the response of asymmetric buildings with rotationally non-linear behavior under earthquake excitation. Furthermore, the results of the SACM were very close to those of the LQR algorithm.

Improved Implementation Algorithm for Continuous-time RHC (연속형 RHC에 대한 개선된 구현 알고리즘)

  • Kim, Tae-Shin;Kim, Chang-You;Lee, Young-Sam
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.9
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    • pp.755-760
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    • 2005
  • This paper proposes an improved implementation algorithm for the continuous-time receding horizon control (RHC). The proposed algorithm has a feature that it has better control performance than the existing algorithm. Main idea of the proposed algorithm is that we can approximate the original RHC problem better by assuming the predicted input trajectory on the prediction horizon has a continuous form, which is constructed from linear interpolation of finite number of vectors. This, in turn, leads to improved control performance. We derive a predictor such that it takes linear interpolation into account and proposes the method by which we can express the cost exactly. Through simulation study fur an inverted pendulum, we illustrate that the proposed algorithm has the better control performance than the existing one.

Normal Mixture Model with General Linear Regressive Restriction: Applied to Microarray Gene Clustering

  • Kim, Seung-Gu
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.205-213
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    • 2007
  • In this paper, the normal mixture model subjected to general linear restriction for component-means based on linear regression is proposed, and its fitting method by EM algorithm and Lagrange multiplier is provided. This model is applied to gene clustering of microarray expression data, which demonstrates it has very good performances for real data set. This model also allows to obtain the clusters that an analyst wants to find out in the fashion that the hypothesis for component-means is represented by the design matrices and the linear restriction matrices.

New Multiple Linear Cryptanalysis of Block Ciphers (블록암호에 대한 새로운 다중선형공격법)

  • Hong, Deuk-Jo;Sung, Jae-Chul;Lee, Sang-Jin;Hong, Seok-Hie
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.17 no.6
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    • pp.11-18
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    • 2007
  • Multiple linear cryptanalysis has been researched as a method building up the linear attack strength. We indicate that the lastest linear attack algorithm using multiple approximations, which was proposed by Biryukov et al. is hardly applicable to block ciphers with highly nonlinear key schedule, and propose a new multiple linear attack algorithm. Simulation of the new attack algorithm with a small block cipher shows that theory for the new multiple linear cryptanalysis works well in practice.

POLYNOMIAL CONVERGENCE OF PREDICTOR-CORRECTOR ALGORITHMS FOR SDLCP BASED ON THE M-Z FAMILY OF DIRECTIONS

  • Chen, Feixiang;Xiang, Ruiyin
    • Journal of applied mathematics & informatics
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    • v.29 no.5_6
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    • pp.1285-1293
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    • 2011
  • We establishes the polynomial convergence of a new class of path-following methods for semidefinite linear complementarity problems (SDLCP) whose search directions belong to the class of directions introduced by Monteiro [9]. Namely, we show that the polynomial iteration-complexity bound of the well known algorithms for linear programming, namely the predictor-corrector algorithm of Mizuno and Ye, carry over to the context of SDLCP.

A NOTE ON GREEDY ALGORITHM

  • Hahm, Nahm-Woo;Hong, Bum-Il
    • Bulletin of the Korean Mathematical Society
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    • v.38 no.2
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    • pp.293-302
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    • 2001
  • We improve the greedy algorithm which is one of the general convergence criterion for certain iterative sequence in a given space by building a constructive greedy algorithm on a normed linear space using an arithmetic average of elements. We also show the degree of approximation order is still $Ο(1\sqrt{\n}$) by a bounded linear functional defined on a bounded subset of a normed linear space which offers a good approximation method for neural networks.

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Implementation of High Speed, Precise Position Control Algorithm for Linear Machine Drive System (선형 전동기 구동 시스템의 고속, 정밀 위치 제어 알고리즘의 구현)

  • 이유인;김준석;김용일
    • Proceedings of the KIPE Conference
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    • 1999.07a
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    • pp.139-142
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    • 1999
  • Recently, the application of the linear machine for industrial field is remarkable increased, especially for the gantry machine and machine tool system. In these application, high precise position control performance is essentially required in steady/transient state. This paper presents the generalized PID position control algorithm which have rare sensitivity to mass and disturbance. Through the experimental results, it is shown that the proposed algorithm have good performance for the linear machine drives in the steady state and transient state in spite of the load mass varing.

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