• Title/Summary/Keyword: state space methods

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A state space meshless method for the 3D analysis of FGM axisymmetric circular plates

  • Wu, Chih-Ping;Liu, Yan-Cheng
    • Steel and Composite Structures
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    • v.22 no.1
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    • pp.161-182
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    • 2016
  • A state space differential reproducing kernel (DRK) method is developed for the three-dimensional (3D) analysis of functionally graded material (FGM) axisymmetric circular plates with simply-supported and clamped edges. The strong formulation of this 3D elasticity axisymmetric problem is derived on the basis of the Reissner mixed variational theorem (RMVT), which consists of the Euler-Lagrange equations of this problem and its associated boundary conditions. The primary field variables are naturally independent of the circumferential coordinate, then interpolated in the radial coordinate using the early proposed DRK interpolation functions, and finally the state space equations of this problem are obtained, which represent a system of ordinary differential equations in the thickness coordinate. The state space DRK solutions can then be obtained by means of the transfer matrix method. The accuracy and convergence of this method are examined by comparing their solutions with the accurate ones available in the literature.

Bayesian Estimation of State-Space Model Using the Hybrid Monte Carlo within Gibbs Sampler

  • Park, Ilsu
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.203-210
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    • 2003
  • In a standard Metropolis-type Monte Carlo simulation, the proposal distribution cannot be easily adapted to "local dynamics" of the target distribution. To overcome some of these difficulties, Duane et al. (1987) introduced the method of hybrid Monte Carlo(HMC) which combines the basic idea of molecular dynamics and the Metropolis acceptance-rejection rule to produce Monte Carlo samples from a given target distribution. In this paper, using the HMC within Gibbs sampler, an asymptotical estimate of the smoothing mean and a general solution to state space modeling in Bayesian framework is obtaineds obtained.

Continuous Time and Discrete Time State Equation Analysis about Electrical Equivalent Circuit Model for Lithium-Ion Battery (리튬 이온 전지의 전기적 등가 회로에 관한 연속시간 및 이산시간 상태방정식 연구)

  • Han, Seungyun;Park, Jinhyeong;Park, Seongyun;Kim, Seungwoo;Lee, Pyeong-Yeon;Kim, Jonghoon
    • The Transactions of the Korean Institute of Power Electronics
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    • v.25 no.4
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    • pp.303-310
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    • 2020
  • Estimating the accurate internal state of lithium ion batteries to increase their safety and efficiency is crucial. Various algorithms are used to estimate the internal state of a lithium ion battery, such as the extended Kalman filter and sliding mode observer. A state-space model is essential in using algorithms to estimate the internal state of a battery. Two principal methods are used to express the state-space model, namely, continuous time and discrete time. In this work, the extended Kalman filter is employed to estimate the internal state of a battery. Moreover, this work presents and analyzes the estimation performance of algorithms consisting of a continuous time state-space model and a discrete time state-space model through static and dynamic profiles.

State Space Exploration of Concurrent Systems with Minimal Visit History (최소방문 기록을 이용한 병행 시스템의 상태 공간 순회 기법)

  • Lee, Jung-Sun;Choi, Yun-Ja;Lee, Woo-Jin
    • Journal of KIISE:Software and Applications
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    • v.37 no.9
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    • pp.669-675
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    • 2010
  • For detecting requirement errors in early system development phase, the behaviors of a system should be described in formal methods and be analyzed with analysis techniques such as reachability analysis and cycle detection. However, since they are usually based on explicit exploration of system state space, state explosion problem may be occurred when a system becomes complex. That is, the memory and execution time for exploration exponentially increase due to a huge state space. In this paper, we analyze the fundamental causes of this problem in concurrent systems and explore the state space without composing concurrent state spaces for reducing the memory requirement for exploration. Also our new technique keeps a visited history minimally for reducing execution time. Finally we represent experimental results which show the efficiency of our technique.

Media Technologies In The Educational Space: The Formation Of Intellectual Independence

  • Parshukova, Lesia;Loboda, Olga;Maha, Petro;Solomenko, Lina;Svanidze, Lia;Levytskyi, Volodymyr
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.323-327
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    • 2021
  • The article examines the process of professional training in educational institutions, media technologies and methods of media communication in the educational space of the institution, characterizes the place of media technologies in the educational space in the context of the term "educational space" itself, systematizes the methods of media communications in education. The peculiarities of media education as a set of means and methods of teaching young people adequate media perception are pointed out.

Improved Region-Based TCTL Model Checking of Time Petri Nets

  • Esmaili, Mohammad Esmail;Entezari-Maleki, Reza;Movaghar, Ali
    • Journal of Computing Science and Engineering
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    • v.9 no.1
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    • pp.9-19
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    • 2015
  • The most important challenge in the region-based abstraction method as an approach to compute the state space of time Petri Nets (TPNs) for model checking is that the method results in a huge number of regions, causing a state explosion problem. Thus, region-based abstraction methods are not appropriate for use in developing practical tools. To address this limitation, this paper applies a modification to the basic region abstraction method to be used specially for computing the state space of TPN models, so that the number of regions becomes smaller than that of the situations in which the current methods are applied. The proposed approach is based on the special features of TPN that helps us to construct suitable and small region graphs that preserve the time properties of TPN. To achieve this, we use TPN-TCTL as a timed extension of CTL for specifying a subset of properties in TPN models. Then, for model checking TPN-TCTL properties on TPN models, CTL model checking is used on TPN models by translating TPN-TCTL to the equivalent CTL. Finally, we compare our proposed method with the current region-based abstraction methods proposed for TPN models in terms of the size of the resulting region graph.

Grouping stocks using dynamic linear models

  • Sihyeon, Kim;Byeongchan, Seong
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.695-708
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    • 2022
  • Recently, several studies have been conducted using state space model. In this study, a dynamic linear model with state space model form is applied to stock data. The monthly returns for 135 Korean stocks are fitted to a dynamic linear model, to obtain an estimate of the time-varying 𝛽-coefficient time-series. The model formula used for the return is a capital asset pricing model formula explained in economics. In particular, the transition equation of the state space model form is appropriately modified to satisfy the assumptions of the error term. k-shape clustering is performed to classify the 135 estimated 𝛽 time-series into several groups. As a result of the clustering, four clusters are obtained, each consisting of approximately 30 stocks. It is found that the distribution is different for each group, so that it is well grouped to have its own characteristics. In addition, a common pattern is observed for each group, which could be interpreted appropriately.

A Sequential Monte Carlo inference for longitudinal data with luespotted mud hopper data (짱뚱어 자료로 살펴본 장기 시계열 자료의 순차적 몬테 칼로 추론)

  • Choi, Il-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.6
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    • pp.1341-1345
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    • 2005
  • Sequential Monte Carlo techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. We can use Monte Carlo particle filters adaptively, i.e. so that they simultaneously estimate the parameters and the signal. However, Sequential Monte Carlo techniques require the use of special panicle filtering techniques which suffer from several drawbacks. We consider here an alternative approach combining particle filtering and Sequential Hybrid Monte Carlo. We give some examples of applications in fisheries(luespotted mud hopper data).

Colour Linear Array Image Enhancement Method with Constant Colour

  • Ji, Jing;Fang, Suping;Cheng, Zhiqiang
    • Current Optics and Photonics
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    • v.6 no.3
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    • pp.304-312
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    • 2022
  • Digital images of cultural relics captured using line scan cameras present limitations due to uneven intensity and low contrast. To address this issue, this report proposes a colour linear array image enhancement method that can maintain a constant colour. First, the colour linear array image is converted from the red-green-blue (RGB) colour space into the hue-saturation-intensity colour space, and the three components of hue, saturation, and intensity are separated. Subsequently, the hue and saturation components are held constant while the intensity component is processed using the established intensity compensation model to eliminate the uneven intensity of the image. On this basis, the contrast of the intensity component is enhanced using an improved local contrast enhancement method. Finally, the processed image is converted into the RGB colour space. The experimental results indicate that the proposed method can significantly improve the visual effect of colour linear array images. Moreover, the objective quality evaluation parameters are improved compared to those determined using existing methods.

A hierarchical approach to state estimation of time-varying linear systems via block pulse function (블럭펄스함수를 이용한 시스템 상태추정의 계층별접근에 관한 연구)

  • 안두수;안비오;임윤식;이재춘
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.3
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    • pp.399-406
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    • 1996
  • This paper presents a method of hierarchical state estimation of the time-varying linear systems via Block-pulse function(BPF). When we estimate the state of the systems where noise is considered, it is very difficult to obtain the solutions because minimum error variance matrix having a form of matrix nonlinear differential equations is included in the filter gain calculation. Therefore, hierarchical approach is adapted to transpose matrix nonlinear differential equations to a sum of low order state space equation from and Block-pulse functions are used for solving each low order state space equation in the form of simple and recursive algebraic equation. We believe that presented methods are very attractive nd proper for state estimation of time-varying linear systems on account of its simplicity and computational convenience. (author). 13 refs., 10 figs.

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