• Title/Summary/Keyword: piecewise linear function

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Controller Design for Fuzzy Systems via Piecewise Quadratic Value Functions

  • Park, Jooyoung;Kim, JongHo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.300-305
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    • 2004
  • This paper concerns controller design for the Takagi-Sugeno (TS) fuzzy systems. The design method proposed in this paper is derived in the framework of the optimal control theory utilizing the piecewise quadratic optimal value functions. The major part of the proposed design procedure consists of solving linear matrix inequalities (LMIs). Since LMIs can be solved efficiently within a given tolerance by the recently developed interior point methods, the design procedure of this paper is useful in practice. A design example is given to illustrate the applicability of the proposed method.

Free and transient responses of linear complex stiffness system by Hilbert transform and convolution integral

  • Bae, S.H.;Cho, J.R.;Jeong, W.B.
    • Smart Structures and Systems
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    • v.17 no.5
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    • pp.753-771
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    • 2016
  • This paper addresses the free and transient responses of a SDOF linear complex stiffness system by making use of the Hilbert transform and the convolution integral. Because the second-order differential equation of motion having the complex stiffness give rise to the conjugate complex eigen values, its time-domain analysis using the standard time integration scheme suffers from the numerical instability and divergence. In order to overcome this problem, the transient response of the linear complex stiffness system is obtained by the convolution integral of a green function which corresponds to the unit-impulse free vibration response of the complex system. The damped free vibration of the complex system is theoretically derived by making use of the state-space formulation and the Hilbert transform. The convolution integral is implemented by piecewise-linearly interpolating the external force and by superimposing the transient responses of discretized piecewise impulse forces. The numerical experiments are carried out to verify the proposed time-domain analysis method, and the correlation between the real and imaginary parts in the free and transient responses is also investigated.

Bayesian Detection of Multiple Change Points in a Piecewise Linear Function (구분적 선형함수에서의 베이지안 변화점 추출)

  • Kim, Joungyoun
    • The Korean Journal of Applied Statistics
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    • v.27 no.4
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    • pp.589-603
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    • 2014
  • When consecutive data follows different distributions(depending on the time interval) change-point detection infers where the changes occur first and then finds further inferences for each sub-interval. In this paper, we investigate the Bayesian detection of multiple change points. Utilizing the reversible jump MCMC, we can explore parameter spaces with unknown dimensions. In particular, we consider a model where the signal is a piecewise linear function. For the Bayesian inference, we propose a new Bayesian structure and build our own MCMC algorithm. Through the simulation study and the real data analysis, we verified the performance of our method.

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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    • v.15 no.2
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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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A analysis of Thin-Straight Monopole antenna on a conducting box Using the Wire-Grid Method (Wire-Grid 방법을 이용한 도체 상자에 부착된 선형 모노폴 안테나 해석)

  • 이승엽;김경재;이영훈;허선종;박한규
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.11
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    • pp.1669-1676
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    • 1993
  • In this paper, a thin-straight monopole antenna attached to a conducting box is analyzed using a moment method with the pocklington integral expression for the exact Green's function. A modeling of a conducting box is based on a Wire-Grid method for an efficient calculation procedure. A system of linear equation is obtained using the piecewise sinusoidal basis function. And a Junction basis function is enforcing to represent the physical current on the edge of the conducting box. Especially, the junction basis functions are overlapped for the current continuity preserving on the vertexes. Numerical results are obtained for the current distribution on the unified antenna/conducting box system, input impedance and radiation pattern. The results are compared with the known data.

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Security Cost Analysis with Linear Ramp Model using Contingency Constrained Optimal Power Flow

  • Lyu, Jae-kun;Kim, Mun-Kyeom;Park, Jong-Keun
    • Journal of Electrical Engineering and Technology
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    • v.4 no.3
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    • pp.353-359
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    • 2009
  • This paper proposes a novel technique for calculating the security costs that properly includes ramping constraints in the operation of a deregulated power system. The ramping process is modeled by a piecewise linear function with certain assumptions. During this process, a ramping cost is incurred if the permissible limits are exceeded. The optimal production costs of the power producers are calculated with the ramping cost included, considering a time horizon with N-1 contingency cases using contingency constrained optimal power flow (CCOPF), which is solved by the primal-dual interior point method (PDIPM). A contingency analysis is also performed taking into account the severity index of transmission line outages and its sensitivity analysis. The results from an illustrative case study based on the IEEE 30-bus system are analyzed. One attractive feature of the proposed approach is that an optimal solution is more realistic than the conventional approach because it satisfies physical constraints, such as the ramping constraint.

Optimal Design of Piecewise Linear Companding Transforms for PAPR Reduction in OFDM Systems

  • Mazahir, Sana;Sheikh, Shahzad Amin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.1
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    • pp.200-220
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    • 2016
  • Orthogonal frequency division multiplexing (OFDM) signals suffer from the problem of large peak-to-average power ratio (PAPR) which complicates the design of the analog front-end of the system. Companding is a well-known PAPR reduction technique that reduces the PAPR by transforming the signal amplitude using a deterministic function. In this paper, a novel piecewise linear companding transform is proposed. The design criteria for the proposed transform is developed by investigating the relationships between the compander and decompander's profile and parameters with the system's performance metrics. Using analysis and simulations, we relate the companding parameters with the bit error rate (BER), out-of-band interference (OBI), amount of companding noise, computational complexity and average power. Based on a set of criteria developed thereof, we formulate the design of the proposed transform. The main aim is to preserve the signal's attributes as much as possible for a predetermined amount of PAPR reduction. Simulations are carried out to evaluate and compare the proposed scheme with the existing companding transforms to demonstrate the enhancement in PAPR, BER and OBI performances.

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

  • Kim, Y.S.;Jhon, S.C.;Lee, E.S.;Min, H.K.;Hong, S.H.
    • Proceedings of the KIEE Conference
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    • 1987.07b
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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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Design of Controller for Affine Takagi-Sugeno Fuzzy System with Parametric Uncertainties via BMI

  • Lee, Sang-In;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.658-662
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    • 2004
  • This paper develops a stability analysis and controller synthesis methodology for a continuous-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties. Affine T-S fuzzy system can be an advantage because it may be able to approximate nonlinear functions to high accuracy with fewer rules than the homogeneous T-S fuzzy systems with linear consequents only. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of bilinear matrix inequalities (BMIs). A simulation example is given to illustrate the application of the proposed method.

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A Study on the Extension of Fuzzy Programming Solution Method (Fuzzy 계확법의 해법일반화에 관한 연구)

  • 양태용;김현준
    • Journal of the Korean Operations Research and Management Science Society
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    • v.11 no.1
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    • pp.36-43
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    • 1986
  • In this study, the fuzzy programming is extended to handle various types of membership functions by transformation of the complicated fuzzy programming problems into the equivalent crisp linear programming problems with single objective. It is well-known that the fuzzy programming problem with linear membership functions (i.e., ramp type) can be easily transformed into a linear programming problem by introducing one dummy variable to minimize the worst unwanted deviation. However, until recently not many researches have been done to handle various general types of complicated linear membership functions which might be more realistic than ramp-or triangular-type functions. In order to handle these complicated membership functions, the goal dividing concept, which is based on the fuzzy set operation (i. e., intersection and union operations), has been prepared. The linear model obtained using the goal dividing concept is more efficient and single than the previous models [4, 8]. In addition, this result can be easily applied to any nonlinear membership functions by piecewise approximation since the membership function is continuous and monotone increasing or decreasing.

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