• Title/Summary/Keyword: Constraint Matrix

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Relative Position Estimation using Kalman Filter Based on Inertial Sensor Signals Considering Soft Tissue Artifacts of Human Body Segments (신체 분절의 연조직 변형을 고려한 관성센서신호 기반의 상대위치 추정 칼만필터)

  • Lee, Chang June;Lee, Jung Keun
    • Journal of Sensor Science and Technology
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    • v.29 no.4
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    • pp.237-242
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    • 2020
  • This paper deals with relative position estimation using a Kalman filter (KF) based on inertial sensors that have been widely used in various biomechanics-related outdoor applications. In previous studies, the relative position is determined using relative orientation and predetermined segment-to-joint (S2J) vectors, which are assumed to be constant. However, because body segments are influenced by soft tissue artifacts (STAs), including the deformation and sliding of the skin over the underlying bone structures, they are not constant, resulting in significant errors during relative position estimation. In this study, relative position estimation was performed using a KF, where the S2J vectors were adopted as time-varying states. The joint constraint and the variations of the S2J vectors were used to develop a measurement model of the proposed KF. Accordingly, the covariance matrix corresponding to the variations of the S2J vectors continuously changed within the ranges of the STA-causing flexion angles. The experimental results of the knee flexion tests showed that the proposed KF decreased the estimation errors in the longitudinal and lateral directions by 8.86 and 17.89 mm, respectively, compared with a conventional approach based on the application of constant S2J vectors.

An Accelerated Iterative Method for the Dynamic Analysis of Multibody Systems (반복 계산법 및 계산 가속기법에 의한 다물체 동역학 해법)

  • 이기수;임철호
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.5
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    • pp.899-909
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    • 1992
  • An iterative solution technique is presented to analyze the dynamic systems of rigid bodies subjected to kinematic constraints. Lagrange multipliers associated with the constraints are iteratively computed by monotonically reducing an appropriately defined constraint error vector, and the resulting equation of motion is solved by a well-established ODE technique. Constraints on the velocity and acceleration as well as the position are made to be satisfied at joints at each time step. Time integration is efficiently performed because decomposition or orthonormalization of the large matrix is not required at all. An acceleration technique is suggested for the faster convergence of the iterative scheme.

An Efficient Identification Algorithm in a Low SNR Channel (저 SNR을 갖는 채널에서 효율적인 인식 알고리즘)

  • Hwang, Jeewon;Cho, Juphil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.4
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    • pp.790-796
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    • 2014
  • Identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling. The method resorts to an adaptive filter with a linear constraint. In this paper, an approach is proposed that is based on decomposition. Indeed, the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present an adaptive algorithm to solve this problem. Proposed technique shows the better performance than one of existing algorithms.

Performance Analysis of STBC Concatenated Convolutional Code for Improvement of Transmission Reliability (STBC의 전송 신뢰성 향상을 위한 컨볼루션 코드 연계 시스템)

  • Shin, Hyun-jun;Oh, Chang-Heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2013.05a
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    • pp.586-589
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    • 2013
  • In this paper, the proposed scheme is STBC system combined with convolutional code to ensure the reliability of data transmission for a high rate wireless communication. In addition, this scheme uses a modified viterbi algorithm in order to get a high system gain when data is transmitted. Because we combine STBC and comvolutional code, the proposed scheme can get a diversity gain of STBC and coding gain of convolutional code at the same time. Unlike existing viterbi docoding algorithm using Hamming distance in order to calculate branch matrix, the modified viterbi algorithm uses Euclidean distance value between received symbol and reference symbol. To analyze the system proposed, it was simulated by changing the constraint length of the convolutional code and the number of transmit and receive antennas of STBC.

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Probabilistic Location Choice and Markovian Industrial Migration a Micro-Macro Composition Approach

  • Jeong, Jin-Ho
    • Journal of the Korean Regional Science Association
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    • v.11 no.1
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    • pp.31-60
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    • 1995
  • The distribution of economic activity over a mutually exclusive and exhaustive categorical industry-region matrix is modeled as a composition of two random components: the probability-like share distribution of jobs and the dynamic evolution of absolute aggregates. The former describes the individual activity location choice by comparing the predicted profitability of the current industry-region pair against that of all other alternatives based on the available information on industry-specific, region specific, or activity specific attributes. The latter describes the time evolution of macro-level aggregates using a dynamic reduced from model. With the seperation of micro choice behavior and macro dynamic aggregate constraint, the usual independence and identicality assumptions become consistent with the activity share distribution, hence multi-regional industrial migration can be represented by a set of probability evolution equations in a conservative Markovian from. We call this a Micro-Macro Composition Approach since the product of the aggregate prediction and the predicted activity share distribution gives the predicted activity distribution gives the predicted activity distribution which explicitly considers the underlying individual choice behavior. The model can be applied to interesting practical problems such as the plant location choice of multinational enterprise, the government industrial ploicy to attract international firms, and the optimal tax-transfer mix to influence activity location choice. We consider the latter as an example.

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Multi-objective Optimization for Force Design of Tensegrity Structures (텐세그리티 구조물 설계를 위한 다목적 최적화 기법에 관한 연구)

  • Ohsaki, Makoto;Zhang, Jingyao;Kim, Jae-Yeol
    • Journal of Korean Association for Spatial Structures
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    • v.8 no.1
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    • pp.49-56
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    • 2008
  • A multi-objective optimization approach is presented for force design of tensegrity structures. The geometry of the structure is given a priori. The design variables are the member forces, and the objective functions are the lowest eigenvalue of the tangent stiffness matrix that is to be maximized, and the deviation of the member forces from the target values that is to be minimized. The multi-objective programming problem is converted to a series of single-objective programming problems by using the constraint approach. A set of Pareto optimal solutions are generated for a tensegrity grid to demonstrate the validity of the proposed method.

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An Improved Multiplicative Updating Algorithm for Nonnegative Independent Component Analysis

  • Li, Hui;Shen, Yue-Hong;Wang, Jian-Gong
    • ETRI Journal
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    • v.35 no.2
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    • pp.193-199
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    • 2013
  • This paper addresses nonnegative independent component analysis (NICA), with the aim to realize the blind separation of nonnegative well-grounded independent source signals, which arises in many practical applications but is hardly ever explored. Recently, Bertrand and Moonen presented a multiplicative NICA (M-NICA) algorithm using multiplicative update and subspace projection. Based on the principle of the mutual correlation minimization, we propose another novel cost function to evaluate the diagonalization level of the correlation matrix, and apply the multiplicative exponentiated gradient (EG) descent update to it to maintain nonnegativity. An efficient approach referred to as the EG-NICA algorithm is derived and its validity is confirmed by numerous simulations conducted on different types of source signals. Results show that the separation performance of the proposed EG-NICA algorithm is superior to that of the previous M-NICA algorithm, with a better unmixing accuracy. In addition, its convergence speed is adjustable by an appropriate user-defined learning rate.

Viscoplastic Solution of Thick Walled Cylinder Considering Axial Constraint (축방향 경계 조건을 고려한 두꺼운 실린더의 점소성 응력해)

  • Yoon, Sam-Son;Lee, Soon-Bok
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.9
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    • pp.1555-1561
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    • 2003
  • Finite element analysis using modern constitutive equation is one of the most general tools to simulate the deformation behavior and to predict the life of the structure. Constitutive equation becomes complicated so as to predict the material behavior more accurately than the classical models. Because of the complexity of constitutive model, numerical treatment becomes so difficult that the calculation should be verified carefully. One-element tests, simple tension or simple shear, are usually used to verify the accuracy of finite element analysis using complicated constitutive model. Since this test is mainly focused on the time integration scheme, it is also necessary to verify the equilibrium iteration using material stiffness matrix and to compare FE results with solution of structures. In this investigation, viscoplastic solution of thick walled cylinder was derived considering axial constraints and was compared with the finite element analysis. All the numerical solutions showed a good coincidence with FE results. This numerical solution can be used as a verification tool for newly developed FE code with complicated constitutive model.

An accurate substructural synthesis approach to random responses

  • Ying, Z.G.;Zhu, W.Q.;Ye, S.Q.;Ni, Y.Q.
    • Structural Engineering and Mechanics
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    • v.39 no.1
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    • pp.47-75
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    • 2011
  • An accurate substructural synthesis method including random responses synthesis, frequency-response functions synthesis and mid-order modes synthesis is developed based on rigorous substructure description, dynamic condensation and coupling. An entire structure can firstly be divided into several substructures according to different functions, geometric and dynamic characteristics. Substructural displacements are expressed exactly by retained mid-order fixed-interfacial normal modes and residual constraint modes. Substructural interfacial degree-of-freedoms are eliminated by interfacial displacements compatibility and forces equilibrium between adjacent substructures. Then substructural mode vibration equations are coupled to form an exact-condensed synthesized structure equation, from which structural mid-order modes are calculated accurately. Furthermore, substructural frequency-response function equations are coupled to yield an exact-condensed synthesized structure vibration equation in frequency domain, from which the generalized structural frequency-response functions are obtained. Substructural frequency-response functions are calculated separately by using the generalized frequency-response functions, which can be assembled into an entire-structural frequency-response function matrix. Substructural power spectral density functions are expressed by the exact-synthesized substructural frequency-response functions, and substructural random responses such as correlation functions and mean-square responses can be calculated separately. The accuracy and capacity of the proposed substructure synthesis method is verified by numerical examples.

A Development of Two-Point Reciprocal Quadratic Approximation Mehtod for Configuration Optimization of Discrete Structures (불연속구조물의 배치최적설계를 위한 이점역이차근사법의 개발)

  • Park, Yeong-Seon;Im, Jae-Mun;Yang, Cheol-Ho;Park, Gyeong-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.12
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    • pp.3804-3821
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    • 1996
  • The configuration optimization is a structural optimization method which includes the coordinates of a structure as well as the sectional properties in the design variable set. Effective reduction of the weight of discrete structures can be obrained by changing the geometry while satisfying stress, Ei;er bickling, displacement, and frequency constraints, etc. However, the nonlinearity due to the configuration variables may cause the difficulties of the convergence and expensive computational cost. An efficient approximation method for the configuration optimization has been developed to overcome the difficulties. The method approximates the constraint functions based onthe second-order Taylor series expansion with reciprocal design variables. The Hessian matrix is approzimated from the information on previous design points. The developed algotithms are coded and the examples are solved.