• 제목/요약/키워드: Piecewise Linear Function Approximation

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Node Monitoring 알고리듬과 NP 방법을 사용한 효율적인 LDPC 복호방법 (Node Monitoring Algorithm with Piecewise Linear Function Approximation for Efficient LDPC Decoding)

  • 서희종
    • 한국전자통신학회논문지
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    • 제6권1호
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    • pp.20-26
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    • 2011
  • 본 논문에서는 NM(node monitoring) 알고리듬과 NP(Piecewise Linear Function Approximation)를 사용해서 LDPC 코드 복호의 복잡도를 감소시키기 위한 효율적인 알고리듬을 제안한다. 이 NM 알고리듬은 새로운 node-threshold 방법과 message passing 알고리듬에 근거해서 제안되었는데, 이에 NP 방법을 사용해서 알고리듬의 복잡도를 더 줄일 수 있었다. 이 알고리듬의 효율성을 입증하기 위해서 모의 실험을 하였다. 모의실험결과, 기존에 잘 알려진 방법에 비해서 20% 정도 더 효율적이었다.

노드 모니터링에 의한 효율적인 LDPC 디코딩 알고리듬 (Efficient LDPC Decoding Algorithm Using Node Monitoring)

  • 서희종
    • 한국전자통신학회논문지
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    • 제10권11호
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    • pp.1231-1238
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    • 2015
  • 본 논문에서는 노드 모니터링(NM)과 Piecewise Linear Function Approximation(: NP)을 사용하여 LDPC 디코딩 알고리듬의 계산복잡도를 감소시키는 알고리듬을 제안한다. 이 알고리듬은 기존의 알고리듬보다도 더 효율적이다. 제안된 알고리즘이 기존의 방법보다도 개선되었다는 것을 확인하기 위해서 모의실험을 하였다. 실험결과, 제안된 알고리즘의 계산은 기존의 방법에 비해 약 20 % 향상되었음을 확인하였다.

Function Approximation Based on a Network with Kernel Functions of Bounds and Locality : an Approach of Non-Parametric Estimation

  • Kil, Rhee-M.
    • ETRI Journal
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    • 제15권2호
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    • pp.35-51
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    • 1993
  • This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

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재난 구호품의 효과적 분배를 위한 혼합정수계획 모형 (A Mixed-Integer Programming Model for Effective Distribution of Relief Supplies in Disaster)

  • 김흥섭
    • 산업경영시스템학회지
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    • 제44권1호
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    • pp.26-36
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    • 2021
  • The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

기동정지계획을 위한 경제급전 알고리즘 (Economic Dispatch Algorithm for Unit Commitment)

  • 박정도;이용훈;김구한;문영현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 C
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    • pp.1506-1509
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    • 1999
  • This paper presents a new economic dispatch algorithm to improve the unit commitment solution while guaranteeing the near optimal solution without reducing calculation speed. The conventional economic dispatch algorithms have the problem that it is not applicable to the unit commitment formulation due to the frequent on/off state changes of units during the unit commitment calculation. Therefore, piecewise linear iterative method have generally been used for economic dispatch algorithm for unit commitment. In that method, the approximation of the generator cost function makes it hard to obtain the optimal economic dispatch solution. In this case, the solution can be improved by introducing a inverse of the incremental cost function. The proposed method is tested with sample system. The results are compared with the conventional piecewise linear iterative method. It is shown that the proposed algorithm yields more accurate and economical solution without calculation speed reduction.

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마이크로 컴퓨터를 이용한 심전도 신호해석 (ANALYSIS OF ECG SIGNAL USING MICROCOMPUTER)

  • 김영서;전승철;이은실;민홍기;홍승홍
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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    • pp.1268-1270
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    • 1987
  • This paper suggests several simple and efficient algorithms for detecting the ECG Signal by Microcomputer's software. The ECG signal detection was performed with the Linear Approximation and the feature extraction. The linear transformation approximates a given waveform by a piecewise-linear function with a preset upper bound on the absolute error between the functional values of the original function and the approximation. And the feature extraction from ECG signal, the features are different wave amplitudes, durations and interwave intervals, used the slope, the amplitude and time-Duration of ECG Sinal.

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고객(顧客)이 임의수(任意數)의 Server 를 원하는 M/M/s system 의 개산법(槪算法) (An approximation of the M/M/s system where customers demand random number of servers)

  • 김성식
    • 대한산업공학회지
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    • 제7권1호
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    • pp.5-11
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    • 1981
  • In the case of numerical implementation, the exact solution method for the M/M/s system where customers demand multiple server use [2] reveals limitations, if a system has large number of servers or types of customers. This is due to the huge matrices involved in the course of the calculations. This paper offers an approximation scheme for such cases. Capitalizing the characteristics of the service rate curve of the system, this method approximates the service rate as a piecewise linear function. With the service rates obtained from the linear function for each number of customers n (n=0. 1. 2,$\cdots$), ${\mu}(n)$, steady-state probabilities and measures of performance are found treating this system as an ordinary M/M/s system. This scheme performs well when the traffic intensity of a system is below about 0.8. Some numerical examples are presented.

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STRONG CONTROLLABILITY AND OPTIMAL CONTROL OF THE HEAT EQUATION WITH A THERMAL SOURCE

  • Kamyad, A.V.;Borzabadi, A.H.
    • Journal of applied mathematics & informatics
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    • 제7권3호
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    • pp.787-800
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    • 2000
  • In this paper we consider an optimal control system described by n-dimensional heat equation with a thermal source. Thus problem is to find an optimal control which puts the system in a finite time T, into a stationary regime and to minimize a general objective function. Here we assume there is no constraints on control. This problem is reduced to a moment problem. We modify the moment problem into one consisting of the minimization of a positive linear functional over a set of Radon measures and we show that there is an optimal measure corresponding to the optimal control. The above optimal measure approximated by a finite combination of atomic measures. This construction gives rise to a finite dimensional linear programming problem, where its solution can be used to determine the optimal combination of atomic measures. Then by using the solution of the above linear programming problem we find a piecewise-constant optimal control function which is an approximate control for the original optimal control problem. Finally we obtain piecewise-constant optimal control for two examples of heat equations with a thermal source in one-dimensional.

표준 매개변수 소속 함수에 기반을 둔 구간 선형 변환 방법과 언어 근사에의 응용 (A Piecewise Linear Transformation Method based on SPMF and Its Application to Linguistic Approximation)

  • 최대영
    • 정보처리학회논문지B
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    • 제8B권4호
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    • pp.351-356
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    • 2001
  • 표준 매개변수 소속 함수(SPMF)에 기반을 둔 구간 선형 변환 방법(PLTM)을 제안한다. 이는 구간 선형 변환 방법을 사용해서 비 매개변수 소속 함수(NPMF)로 표현된 퍼지 집합이 매개변수 소속 함수(PMF)로 표현된 퍼지 집합으로 변환될 수 있다는 생각에서 유래되었다. 이 경우, 이들 매개변수들은 퍼지 집합의 구조를 결정하기 위한 특징점들 이라고 할 수 있다. 결과적으로 구간 선형 변환 방법은 비 매개변수 소속 함수를 매개변수 소속 함수로 변환해 줌으로써 비 매개변수 소속 함수에 기반을 둔 퍼지 시스템과 비교해 볼 때 퍼지 시스템이 상대적으로 빠르게 처리될 수 있게 한다. 한편, 표준 매개변수 소속 함수들의 전형적인 형태가 소개되고 분석된다. 끝으로, PLTM의 전형적인 응용을 제시하고 수치적인 예를 보여준다.

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무선통신에서의 Non-Linear Detector System 설계 (The System of Non-Linear Detector over Wireless Communication)

  • 공형윤
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 하계종합학술대회논문집
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    • pp.106-109
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    • 1998
  • Wireless communication systems, in particular, must operate in a crowded electro-magnetic environmnet where in-band undesired signals are treated as noise by the receiver. These interfering signals are often random but not Gaussian Due to nongaussian noise, the distribution of the observables cannot be specified by a finite set of parameters; instead r-dimensioal sample space (pure noise samples) is equiprobably partitioned into a finite number of disjointed regions using quantiles and a vector quantizer based on training samples. If we assume that the detected symbols are correct, then we can observe the pure noise samples during the training and transmitting mode. The algorithm proposed is based on a piecewise approximation to a regression function based on quantities and conditional partition moments which are estimated by a RMSA (Robbins-Monro Stochastic Approximation) algorithm. In this paper, we develop a diversity combiner with modified detector, called Non-Linear Detector, and the receiver has a differential phase detector in each diversity branch and at the combiner each detector output is proportional to the second power of the envelope of branches. Monte-Carlo simulations were used as means of generating the system performance.

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