• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.947-952
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• 2021

In this paper, the simplified kinematic error model for Delta parallel robot is presented, which can enable the analytical forward kinematics essentially for kinematic calibration calculations instead of the numerical one. The simplified kinematic error model is proposed and the forward kinematics including the error parameters is analytically derived. The kinematic calibration algorithm of the Delta parallel robot with 90 degree arrangement using laser tracker and the experiment result are presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1504-1526
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• 2018

For uplink multi-user massive MIMO systems, conventional minimum mean square error (MMSE) linear detection method achieves near-optimal performance when the number of antennas at base station is much larger than that of the single-antenna users. However, MMSE detection involves complicated matrix inversion, thus making it cumbersome to be implemented cost-effectively and rapidly. In this paper, we first summarize in detail the state-of-the-art simplified MMSE detection algorithms that circumvent the complicated matrix inversion and hence reduce the computation complexity from ${\mathcal{O}}(K^3)$ to ${\mathcal{O}}(K^2)$ or ${\mathcal{O}}(NK)$ with some certain performance sacrifice. Meanwhile, we divide the simplified algorithms into two categories, namely the matrix inversion approximation and the classical iterative linear equation solving methods, and make comparisons between them in terms of detection performance and computation complexity. In order to further optimize the detection performance of the existing detection algorithms, we propose more proper solutions to set the initial values and relaxation parameters, and present a new way of reconstructing the exact effective noise variance to accelerate the convergence speed. Analysis and simulation results verify that with the help of proper initial values and parameters, the simplified matrix inversion based detection algorithms can achieve detection performance quite close to that of the ideal matrix inversion based MMSE algorithm with only a small number of series expansions or iterations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.6
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• pp.947-954
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• 2016

A simplified analysis method is first proposed in order to determine an optimized initial shape of cable-stayed bridges including all unstrained element lengths without using complicated nonlinear FE analysis. The unstrained-length based FE method is then presented using the unstrained lengths by the simplified analysis. To demonstrate validity and accuracy of the proposed method, Incheon bridge model having the fabrication camber is constructed and initial shaping analysis is performed using the presented method and commercial finite element analysis program, MIDAS. Resultantly it is shown that the initial solutions by the proposed algorithm are well optimized and in good agreement with those by MIDAS except for axial displacements of the main member.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.5
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• pp.51-58
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• 2004

In this paper, a mesh simplification algorithm is proposed which considers the conservation of the volume of a 3D model. In General, most of mesh simplification algorithm use a distance metric. The distance metric is very efficient to measure geometric error, but it causes volume changes between the original model and the simplified model. In this paper a mesh simplification algorithm which conserves the volume of the original model is suggested. A new vertex resulting from an edge contraction, takes a position which conserves the volume of the 3D model using the proposed algorithm. Although the new algorithm needs more time than the QEM algorithm, it is shown that it conserves the original volumn of the 3D model during the simplification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3889-3903
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• 2017

Fast and accurate localization of randomly deployed nodes is required by many applications in wireless sensor networks (WSNs). However, mobile nodes localization in WSNs is more difficult than static nodes localization since the nodes mobility brings more data. In this paper, we propose a Range-based Monte Carlo Box (RMCB) algorithm, which builds upon the Monte Carlo Localization Boxed (MCB) algorithm to improve the localization accuracy. This algorithm utilizes Received Signal Strength Indication (RSSI) ranging technique to build a sample box and adds a preset error coefficient in sampling and filtering phase to increase the success rate of sampling and accuracy of valid samples. Moreover, simplified Particle Swarm Optimization (sPSO) algorithm is introduced to generate new samples and avoid constantly repeated sampling and filtering process. Simulation results denote that our proposed RMCB algorithm can reduce the location error by 24%, 14% and 14% on average compared to MCB, Range-based Monte Carlo Localization (RMCL) and RSSI Motion Prediction MCB (RMMCB) algorithm respectively and are suitable for high precision required positioning scenes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1185-1190
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• 2008

In this paper, we propose an simplified successive minimum mean square error ($S^{2}MMSE$) algorithm that can simplify the computational complexity for precoding matrix generation in the successive minimum mean square error (SMMSE) precoding method, which is adopted as a multiuser multiple-input multiple-output (MU-MIMO) precoding technique in the IST (information society technologies)-WINNER (wireless world initiative new radio) project. The original algorithm generates the precoding matrix by calculating all individual precoding vectors with each requiring its own MMSE nulling matrix, over all receive antennas for all users. In contrast, this proposed algorithm first calculates the MMSE nulling matrix for each user, and then calculates all precoding vectors for respective receive antennas of the corresponding user by using the identical MMSE nulling matrix, in which only a simple matrix-vector multiplication is required for each vector. Consequently, it can simplify significantly the computational complexity to generate a precoding matrix for SMMSE precoding.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.199-204
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• 2013

An implementation method of real-time numeral recognizer based on gesture is presented in this paper for various information devices. The proposed algorithm steadily captures the motion of a hand on 3D open space with the Kinect sensor. The captured hand motion is simplified with PCA, in order to preserve the trace consistency and to minimize the trace variations due to noises and size changes. In addition, we also propose a new HMM using both the gradient and the positional features of the simplified hand stroke. As the result, the proposed algorithm has robust characteristics to the variations of the size and speed of hand motion. The recognition rate is increased up to 30%, because of this combined model. Experimental results showed that the proposed algorithm gives a high recognition rate about 98%.

• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.289-300
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• 2003

In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.03a
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• pp.331-338
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• 1999

In the present study, a searching technique for critical slip surface in two dimensional slope stability analysis is proposed. The failure surface generation and analysis has been usually limited to simple geometric shapes. However, more random surfaces need to be examined for some particular ground conditions. For this purpose, random searching technique is developed using genetic algorithm. The generalized limit equilibrium method is employed as the method of stability analysis. Using this technique, the factor of safety is compared with the result by using simplified Bishop's method. In addition, the convergent trend of fitness value is analyzed.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.1
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• pp.3-10
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• 2003

Application of matrix converter to vector control of induction motor using simplified Venturini algorithm which is capable of achieving the maximum output voltage is developed. This algorithm simplifies the control algorithm and therefor reduces the digital implementation time. Matrix converter is used as voltage-referenced voltage fed vector controlled induction motor drive. This paper describes the performance of vector controlled induction motor with four quadrant capability employing a matrix converter power circuit. The advantage of this system over the conventional rectifier-inverter arrangement are capability for regeneration into the utility, sinusoidal supply currents and minimum passive components. The steady-state and transient performance of the induction motor drive under the vector control technique is demonstrate with simulation and experiment results.