• 제목/요약/키워드: Linear algorithm

검색결과 4,052건 처리시간 0.034초

A NEW APPROACH FOR NUMERICAL SOLUTION OF LINEAR AND NON-LINEAR SYSTEMS

  • ZEYBEK, HALIL;DOLAPCI, IHSAN TIMUCIN
    • Journal of applied mathematics & informatics
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    • 제35권1_2호
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    • pp.165-180
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    • 2017
  • In this study, Taylor matrix algorithm is designed for the approximate solution of linear and non-linear differential equation systems. The algorithm is essentially based on the expansion of the functions in differential equation systems to Taylor series and substituting the matrix forms of these expansions into the given equation systems. Using the Mathematica program, the matrix equations are solved and the unknown Taylor coefficients are found approximately. The presented numerical approach is discussed on samples from various linear and non-linear differential equation systems as well as stiff systems. The computational data are then compared with those of some earlier numerical or exact results. As a result, this comparison demonstrates that the proposed method is accurate and reliable.

LVQ와 ADALINE을 이용한 학습 알고리듬 (Learning Algorithm using a LVQ and ADALINE)

  • 윤석환;민준영;신용백
    • 산업경영시스템학회지
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    • 제19권39호
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    • pp.47-61
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    • 1996
  • We propose a parallel neural network model in which patterns are clustered and patterns in a cluster are studied in a parallel neural network. The learning algorithm used in this paper is based on LVQ algorithm of Kohonen(1990) for clustering and ADALINE(Adaptive Linear Neuron) network of Widrow and Hoff(1990) for parallel learning. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists of 250 patterns of ASCII characters normalized into $8\times16$ and 1124. The proposed algorithm consists of two parts. First, N patterns to be learned are categorized into C clusters by LVQ clustering algorithm. Second, C patterns that was selected from each cluster of C are learned as input pattern of ADALINE(Adaptive Linear Neuron). Data used in this paper consists 250 patterns of ASCII characters normalized into $8\times16$ and 1124 samples acquired from signals generated from 9 car models that passed Inductive Loop Detector(ILD) at 10 points. In ASCII character experiment, 191(179) out of 250 patterns are recognized with 3%(5%) noise and with 1124 car model data. 807 car models were recognized showing 71.8% recognition ratio. This result is 10.2% improvement over backpropagation algorithm.

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An Evolutionary Optimized Algorithm Approach to Compensate the Non-linearity in Linear Variable Displacement Transducer Characteristics

  • Murugan, S.;Umayal, S.P.
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.2142-2153
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    • 2014
  • Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

ABS ALGORITHMS FOR DIOPHANTINE LINEAR EQUATIONS AND INTEGER LP PROBLEMS

  • ZOU MEI FENG;XIA ZUN QUAN
    • Journal of applied mathematics & informatics
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    • 제17권1_2_3호
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    • pp.93-107
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    • 2005
  • Based on the recently developed ABS algorithm for solving linear Diophantine equations, we present a special ABS algorithm for solving such equations which is effective in computation and storage, not requiring the computation of the greatest common divisor. A class of equations always solvable in integers is identified. Using this result, we discuss the ILP problem with upper and lower bounds on the variables.

A Linear-Time Algorithm to Find the First Overlap in a Binary Word

  • Park, Thomas H.
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
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    • pp.165-168
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    • 2000
  • First, we give a linear-time algorithm to find the first overlap in an arbitrary binary word. Second, we implement the algorithm in the C language and show that the number of comparisons in this algorithm is less than 31n, where n$\geq$3 is the length of the input word.

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A Formulation of Hybrid Algorithm for Linear Programming

  • Kim, Koon-Chan
    • 한국경영과학회지
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    • 제19권3호
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    • pp.187-201
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    • 1994
  • This paper introduces an effective hybridization of the usual simplex method and an interior point method in the convergent framework of Dembo and Sahi. We formulate a specific and detailed algorithm (HYBRID) and report the results of some preliminary testing on small dense problems for its viability. By piercing through the feasible region, the newly developed hybrid algorithm avoids the combinatorial structure of linear programs, and several other interesting and important characteristics of this algorithm are also discussed.

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미지의 선형 시스템에 대한 On-Line 모델링 알고리즘 (On-Line Identification Algorithm of Unknown Linear Systems)

  • 최수일;김병국
    • 전자공학회논문지B
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    • 제31B권4호
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    • pp.48-54
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    • 1994
  • A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear systems with unkonwn time delay, order, and parameters. The algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extendedto recursive form by using two dimensional autocorrelations and crosscorrelations of input and output with constant data length. The proposed algorith can cope with slowly time-varying or order-varying delayed system. Various simulations reveal the performance of the algorithm.

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선형 평균스텝 양자화를 사용한 MPEG-2 비트율 제어 (A bit-rate control of MPEG-2 using linear average step quantization)

  • 이두열;이근영
    • 전자공학회논문지S
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    • 제34S권9호
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    • pp.84-90
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    • 1997
  • We proposed a new bit-rate control algorithm to improve MPEG-2 video software encoder. Bit-rate Control plays an improtant role in picture quality of MPEG-2 encoder. To achieve better encoding performance such as controlling picture quality and using bity properly, we proposed a MPEG-2 bit-rate control algorithm using linear average Step-Size. Using a benchmark Program, we compared our algorithm with MPEG-2 Test Model 5. Our proposed algorithm showed better Bit-Rate Control with respect to used bits, picture quality.

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LMI 가능성 문제를 위한 타원 알고리즘의 개선 (An improved ellipsoid algorithm for LMI feasibility problems)

  • 방대인;최진영
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.188-192
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    • 2002
  • The ellipsoid algorithm solves some feasibility(or optimization) problems with LMI(Linear Matrix Inequality) constraint in polynomial time. Recently, it has been replaced by interior point algorithm due to its slow convergence and incapability of verifying feasibility. This paper proposes a method to improve its convergence by using the deep-cut method of linear programming. Simulation results show that the improved algorithm is more effective than the original one.

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반복 알고리즘을 적용한 D-STTD 시스템의 검출 기법 제안 및 성능 분석 (The Proposal and Performance Analysis for the Detection Scheme of D-STTD using Iterative Algorithm)

  • 윤길상;이정환;유철우;황인태
    • 한국통신학회논문지
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    • 제33권9A호
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    • pp.917-923
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    • 2008
  • D-STTD 시스템은 Alamouti Code로 알려진 STTD기법을 적용하여 다이버시티 효과를 획득하면서 STTD기법을 병렬로 한번 더 사용함으로써 멀티플렉싱 효과도 얻을 수 있는 기법이다. 이러한 서로 다른 정보를 보내는 멀티플렉싱 효과로 인해 D-STTD는 기존 STTD 기법의 Combining 기법을 적용하는데 어려움을 가져온다. 그래서 본 논문에서는 MMSE 기법을 바탕으로 멀티플렉싱 검출 기법으로 잘 알려진 Linear 알고리즘, SIC 알고리즘, OSIC 알고리즘을 D-STTD 시스템에 적용하고 그 성능을 비교한다. 그리고 새롭게 MAP 알고리즘을 D-STTD 시스템에 적용하여 성능을 분석하고자 한다. 모의 실험 결과, Linear MMSE Detector보다 반복 알고리즘을 적용한 Detector가 최대 3.7dB의 성능향상을 보였다. 특히, 반복 Detector 중 MAP 알고리즘을 적용한 경우에는 약 4.4dB의 성능차까지 나타냈다.