• Title/Summary/Keyword: basis-adaptive selection

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Shape Reconstruction from Unorganized Cloud of Points using Adaptive Domain Decomposition Method (적응적 영역분할법을 이용한 임의의 점군으로부터의 형상 재구성)

  • Yoo Dong-Jin
    • Journal of the Korean Society for Precision Engineering
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    • v.23 no.8 s.185
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    • pp.89-99
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    • 2006
  • In this paper a new shape reconstruction method that allows us to construct surface models from very large sets of points is presented. In this method the global domain of interest is divided into smaller domains where the problem can be solved locally. These local solutions of subdivided domains are blended together according to weighting coefficients to obtain a global solution using partition of unity function. The suggested approach gives us considerable flexibility in the choice of local shape functions which depend on the local shape complexity and desired accuracy. At each domain, a quadratic polynomial function is created that fits the points in the domain. If the approximation is not accurate enough, other higher order functions including cubic polynomial function and RBF(Radial Basis Function) are used. This adaptive selection of local shape functions offers robust and efficient solution to a great variety of shape reconstruction problems.

Two variations of cross-distance selection algorithm in hybrid sufficient dimension reduction

  • Jae Keun Yoo
    • Communications for Statistical Applications and Methods
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    • v.30 no.2
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    • pp.179-189
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    • 2023
  • Hybrid sufficient dimension reduction (SDR) methods to a weighted mean of kernel matrices of two different SDR methods by Ye and Weiss (2003) require heavy computation and time consumption due to bootstrapping. To avoid this, Park et al. (2022) recently develop the so-called cross-distance selection (CDS) algorithm. In this paper, two variations of the original CDS algorithm are proposed depending on how well and equally the covk-SAVE is treated in the selection procedure. In one variation, which is called the larger CDS algorithm, the covk-SAVE is equally and fairly utilized with the other two candiates of SIR-SAVE and covk-DR. But, for the final selection, a random selection should be necessary. On the other hand, SIR-SAVE and covk-DR are utilized with completely ruling covk-SAVE out, which is called the smaller CDS algorithm. Numerical studies confirm that the original CDS algorithm is better than or compete quite well to the two proposed variations. A real data example is presented to compare and interpret the decisions by the three CDS algorithms in practice.

An Adaptive Virtual Machine Location Selection Mechanism in Distributed Cloud

  • Liu, Shukun;Jia, Weijia
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.12
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    • pp.4776-4798
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    • 2015
  • The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

Uncertainty Observer using the Radial Basis Function Networks for Induction Motor Control

  • Huh, Sung-Hoe;Lee, Kyo-Beum;Ick Choy;Park, Gwi-Tae;Yoo, Ji-Yoon
    • Journal of Power Electronics
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    • v.4 no.1
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    • pp.1-11
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    • 2004
  • A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper. Torque ripple in the DTC system for high power induction motor could be drastically reduced with the foregoing researches of switching voltage selection and torque ripple reduction algorithms. However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. In this paper, the inherent uncertainty is approximated on-line by the RBFN, and an additional robust control term is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented. Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system.

Novel Adaptive De-interlacing Algorithm using Temporal Correlation

  • Ku, Su-Il;Jung, Tae-Young;Jeong, Je-Chang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.199-202
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    • 2009
  • This paper proposes a novel adaptive algorithm for deinterlacing. In the proposed algorithm, the previously developed Enhanced ELA [6], Chen [9] and Li [10] algorithms were used as a basis. The fundamental mechanism was the selection and application of the appropriate algorithm according to the correlation with the previous and next field using temporal information. Extensive simulations were conducted for video sequences and showed good performance in terms of peak signal-to-ratio (PSNR) and subjective quality.

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Biological indicators to monitor responses against climate change in Korea

  • Lee, Byoung-Yoon;Nam, Gi-Heum;Yun, Jong-Hak;Cho, Ga Youn;Lee, Jin Sung;Kim, Jin-Han;Park, Tae Seo;Kim, Kigyoung;Oh, Kyounghee
    • Korean Journal of Plant Taxonomy
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    • v.40 no.4
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    • pp.202-207
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    • 2010
  • The most useful criteria and selection procedures of biological indicators have been developed in Korea because they have taken into account local and national concerns on biological responses against climate change. On the basis of these criteria and selection procedures, 100 climate-sensitive biological indicator species were selected to predict biodiversity distribution shift by climate change and manage biological resources integratedly at the national level. It is expected that selection and monitoring of biological indicators by climate change will provide significant information to prepare protective strategies of vulnerable species against climate change and adaptive policies under the changing environment in Korea. In this paper, we have reviewed what kinds of criteria were considered in selecting bioindicators to assess responses of biological organisms against climate change. Definition and selection steps of bioindicators were proposed, and the 100 species of climate- sensitive biological indicators were selected out of 33,253 taxa reported in Korea.

Analysis and implementation of fast discrete coisne transform on TMS320C80 (TMS320C80 시스템에서의 고속 이산 여현 변환의 해석 및 구현)

  • 유현범;박현욱
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.1
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    • pp.124-131
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    • 1997
  • There have been many demands for th ereal-time image compression. The image compression systems have a wide range of applications. However, real-time encoding is hard to implement because it needs a large amount of computations. In particular, the discrete cosine transform (DCT) and motion estimatio require a large number of arithmetic oeprations compared to other algorithms in MPEG-2. The conventional fasdt DCT algorithms have focused on the reduction of the number of additions more cycles and more expense in realization. Because TMS320C80 has special structure, new approach for implementation of DCT is suggested. The selection of adaptive algorithm and optimization is requried TMS320C80 are analyzed an dsome adaptive DCT algorithms are selected. The DCT algorithms are optimized and implemented. Chens and lees DCT algorithms among various fast algorithms are selected because 1-D approach is effective in the view of th einternal structure of TMS320C80. According to the simulation result, Lees algorithm is more effective in speed and has little difference in precision. On the basis of the result, the possibility of DCT implementation for real-time MPEG-2 system is verified and the required number of the processor, called advanced DSP, is decided for real-time MPEG-2 encoding and decoding.

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Intelligent On-demand Routing Protocol for Ad Hoc Network

  • Ye, Yongfei;Sun, Xinghua;Liu, Minghe;Mi, Jing;Yan, Ting;Ding, Lihua
    • Journal of Information Processing Systems
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    • v.16 no.5
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    • pp.1113-1128
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    • 2020
  • Ad hoc networks play an important role in mobile communications, and the performance of nodes has a significant impact on the choice of communication links. To ensure efficient and secure data forwarding and delivery, an intelligent routing protocol (IAODV) based on learning method is constructed. Five attributes of node energy, rate, credit value, computing power and transmission distance are taken as the basis of segmentation. By learning the selected samples and calculating the information gain of each attribute, the decision tree of routing node is constructed, and the rules of routing node selection are determined. IAODV algorithm realizes the adaptive evaluation and classification of network nodes, so as to determine the optimal transmission path from the source node to the destination node. The simulation results verify the feasibility, effectiveness and security of IAODV.

Sparse decision feedback equalization for underwater acoustic channel based on minimum symbol error rate

  • Wang, Zhenzhong;Chen, Fangjiong;Yu, Hua;Shan, Zhilong
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.617-627
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    • 2021
  • Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

Wavelet Network for Stable Direct Adaptive Control of Nonlinear Systems (비선형 시스템의 안정한 직접 적응 제어를 위한 웨이브렛 신경회로망)

  • Seo, Seung-Jin;Seo, Jae-Yong;Won, Kyoung-Jae;Yon, Jung-Heum;Jeon, Hong-Tae
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.10
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    • pp.51-57
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    • 1999
  • In this paper, we deal with the problem of controlling an unknown nonlinear dynamical system, using wavelet network. Accurate control of the nonlinear systems depends critically on the accuracy and efficiency of the function approximator used to approximate the function. Thus, we use wavelet network which shows high capability of approximating the functions and includes the free-selection of basis functions for the control of the nonlinear system. We find the dilation and translation that are wavelet network parameters by analyzing the time-frequency characteristics of the controller's input to construct an initial adaptive wavelet network controller. Then, weights is adjusted by the adaptive law based on the Lyapunov stability theory. We apply this direct adaptive wavelet network controller to control the inverted pendulum system which is an nonlinear system.

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