• Title/Summary/Keyword: recursive equation

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Nonlinear Lattice Algorithms using QRD and Channel Decomposition (QR 분해와 채널 분해법을 이용한 비선형 격자 알고리듬)

  • 안봉만;백흥기
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.10
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    • pp.1326-1337
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    • 1995
  • In this paper, we transformed the bilinear filter into an equivalent linear multichannel filter and derived QR decomposition based recursive least squares algorithms for bilinear lattice filters. We also defined order update relation of the forward and the backward input vectors by using the channel decomposition. The forward and the backward data matrices were defined by using the forward and the backward input vectors and orthogonalized with the QR decomposition. we can obtain the lattice equations of the bilinear filters by using the channel decomposition. we can be derived the lattice equations of the bilinear filters using this decomposition process which are the same as the lattice equations derived by Baik, we can use the coefficient transformation algorithm proposed by Baik. We derived the equation error and the output error algorithm of the QRD based RLS bilinear lattice algorithm. Also, we evaluated the performance of the proposed algorithms through the system identification of the bilinear system.

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Robust Kalman Filtering with Perturbation Estimation Process-for Uncertain Systems (섭동 추정 프로세스를 이용한 불확실 시스템에 대한 강인 칼만 필터링 기법)

  • Kwon Sang-Joo
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.3
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    • pp.201-207
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    • 2006
  • A robust Kalman filtering method for uncertain stochastic systems is suggested by adopting a perturbation estimation process which is to reconstruct total uncertainty with respect to the nominal state transition equation. The predictor and corrector of discrete Kalman filter are reformulated with the perturbation estimator. Successively, the state and perturbation estimation error dynamics and the corresponding error covariance propagation equations are derived as well. Finally we have the recursive algorithm of Combined Kalman Filter-Perturbation Estimator (CKF). The proposed combined Kalman filter-perturbation estimator has the property of integrating innovations and the adaptation capability to system uncertainties. A numerical example is shown to demonstrate the effectiveness of the proposed scheme.

Optimization Methodology of Multiple Air Hole Effects in Substrate Integrated Waveguide Applications

  • Kim, Jin-Yang;Chun, Dong-Wan;Ryu, Christopher Jayun;Lee, Hai-Young
    • Journal of electromagnetic engineering and science
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    • v.18 no.3
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    • pp.160-168
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    • 2018
  • A wide spectrum of potential applications using substrate integrated waveguide (SIW) technologies in conjunction with air hole regions is introduced, and an efficient optimization methodology to cope with the multiple air hole effect in SIW applications is proposed. The methodology adopts a genetic algorithm to obtain optimum air hole dimensions for the specific propagation constant that can be accurately calculated using the recursive and closed form equations presented. The optimization results are evaluated by designing an SIW bandpass filter, and they show excellent performance. The optimization methodology using the proposed equations is effective in performance enhancement for the purposes of low loss and broadband SIW applications.

Dynamic Optimal Pricing for New Products in a Duopoly (복점시장에서 신상품의 동태적 최적가격설정에 관한 연구)

  • Jun, Duk-Bin;Choi, Li-Koon
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.3
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    • pp.545-557
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    • 1997
  • This paper deals with dynamic optimal pricing for new products by a firm which maximizes the discounted profit stream of it's own in a duopoly. The problem is constructed as differential games and dynamic optimization theory. Cost is assumed to decline as time goes on. A modified customer's choice model is formulated as a diffusion model and we solve a dynamic optimization problem by adopting the diffusion model. Since this paper focus on deriving real prices not showing a time trend, we formulate recursive form equations of costate variables(shadow price) and a simultaneous equation of price. Hence we derive a dynamic optimal pricing model for using in real market. In particular, we construct a dynamic optimal pricing model in the case that there are benefits from not only new subscribers but also previous subscribers. We analyze instant camera market in U.S.A(1976-1985) by utilizing the above model.

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Performance Analysis of Flow and Error Control Procedures in a Packet-Switching Network (패킷 교환망에서 흐름과 에러 제어과정에 관한 성능분석)

  • Lie, Chang-Hoon;Hong, Jeong-Wan;Hong, Jung-Sik;Lee, Kang-Won
    • IE interfaces
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    • v.4 no.1
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    • pp.63-69
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    • 1991
  • In this paper, the Go-Back-N ARQ protocol with decoding in communication network is considered. The time delay and throughput are respectively analyzed as a function of window size and decoding time out. Packets arrive continuously at the decoder, and are stored in a buffer if the decoder is busy upon its arrival. The decoder devotes no more than a time-out period of predetermined length to the decoding of any single packet. If packet decoding is completed within that period, the packet leaves the system. Otherwise, it is retransimitted and its decoding starts anew. The time delay and throughput are obtained using recursive formula and difference equation. An appropriate time out and window size that satisfies the grade of service can be determined.

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Buckling of fully and partially embedded non-prismatic columns using differential quadrature and differential transformation methods

  • Rajasekaran, S.
    • Structural Engineering and Mechanics
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    • v.28 no.2
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    • pp.221-238
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    • 2008
  • Numerical solution to buckling analysis of beams and columns are obtained by the method of differential quadrature (DQ) and harmonic differential quadrature (HDQ) for various support conditions considering the variation of flexural rigidity. The solution technique is applied to find the buckling load of fully or partially embedded columns such as piles. A simple semi- inverse method of DQ or HDQ is proposed for determining the flexural rigidities at various sections of non-prismatic column ( pile) partially and fully embedded given the buckling load, buckled shape and sub-grade reaction of the soil. The obtained results are compared with the existing solutions available from other numerical methods and analytical results. In addition, this paper also uses a recently developed technique, known as the differential transformation (DT) to determine the critical buckling load of fully or partially supported heavy prismatic piles as well as fully supported non-prismatic piles. In solving the problem, governing differential equation is converted to algebraic equations using differential transformation methods (DT) which must be solved together with applied boundary conditions. The symbolic programming package, Mathematica is ideally suitable to solve such recursive equations by considering fairly large number of terms.

A Study on Adaptive Control For Robotic Manipulator System (로보트 머니플레이터 시스템에 대한 적응 제어에 관한 연구)

  • Kang, Moon-Sik;Park, Chan-Young;Park, Mig-Non;Lee, Sang-Bae
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1210-1212
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    • 1987
  • Adaptive control for robot manipulator controller has been considered as an effective approach because robot dynamic models contain the nonlinearities and uncertainties. This paper present an approach for the position and velocity control of a manipulator by using the seif-tuning type controller for each point. The complicated model manipulator system is modeled by a set of time series difference equation. The parameters of the models are determined by online recursive algorithms. Finally some remarks on the effectiveness and applications of adaptive controller are discussed.

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Tracking Filter Design for a Maneuvering target Using Jump Processes

  • Lim, Sang-Seok
    • Journal of Electrical Engineering and information Science
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    • v.3 no.3
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    • pp.373-384
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    • 1998
  • This paper presents a maneuvering target model with the maneuver dynamics modeled as a jump process of Poisson-type. The jump process represents the deterministic maneuver(or pilot commands) and is described by a stochastic differential equation driven by a Poisson process taking values a set of discrete states. Employing the new maneuver model along with the noisy observations described by linear difference equations, the author has developed a new linear, recursive, unbiased minimum variance filter, which is structurally simple, computationally efficient, and hence real-time implementable. Futhermore, the proposed filter does not involve a computationally burdensome technique to compute the filter gains and corresponding covariance matrices and still be able to track effectively a fast maneuvering target. The performance of the proposed filter is assessed through the numerical results generated from the Monte-Carlo simulation.

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Analysis of Multiple Step-Index Waveguide by the WKB Approximation (WKB 근사를 이용한 다중 계단형 광도파로의 해석)

  • Seo, Jeong-Hun;Lee, Se-Ho;Lee, Byeong-Gwon;Kim, Chang-Min
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.48 no.2
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    • pp.141-146
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    • 1999
  • The eigenvalue equations of multiple waveguides with step-index profile are derived by using the WKB theory. Phase changes unique to step-index discontinuity areintroduced when applying the WKB connection formula to turning points. The transfer matrix method is employed for the analysis of multiple structure and the derived eigenvalue equation are represented in the recursive form. The results by the WKB are compared with those by the FEM for a three-waveguide coupler.

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Self-tuning optimal control of an active suspension using a neural network

  • Lee, Byung-Yun;Kim, Wan-Il;Won, Sangchul
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.295-298
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    • 1996
  • In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

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