• Title/Summary/Keyword: optimal gain selection

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Performance analysis of precoding-aided differential spatial modulation systems with transmit antenna selection

  • Kim, Sangchoon
    • ETRI Journal
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    • v.44 no.1
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    • pp.117-124
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    • 2022
  • In this paper, the performance of precoding-aided differential spatial modulation (PDSM) systems with optimal transmit antenna subset (TAS) selection is examined analytically. The average bit error rate (ABER) performance of the optimal TAS selection-based PDSM systems using a zero-forcing (ZF) precoder is evaluated using theoretical upper bound and Monte Carlo simulations. Simulation results validate the analysis and demonstrate a performance penalty < 2.6 dB compared with precoding-aided spatial modulation (PSM) with optimal TAS selection. The performance analysis reveals a transmit diversity gain of (NT-NR+1) for the ZF-based PDSM (ZF-PDSM) systems that employ TAS selection with NT transmit antennas, NS selected transmit antennas, and NR receive antennas. It is also shown that reducing the number of activated transmit antennas via optimal TAS selection in the ZF-PDSM systems degrades ABER performance. In addition, the impacts of channel estimation errors on the performance of the ZF-PDSM system with TAS selection are evaluated, and the performance of this system is compared with that of ZF-based PSM with TAS selection.

Optimal Control Design-based Gain Selection of an LCL-filtered Grid-connected Inverter in State-Space under Distorted Grid Environment

  • Tran, Vi-Thuy;Yoon, Seung-Jin;Kim, Kyeong-Hwa
    • Proceedings of the KIPE Conference
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    • 2018.07a
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    • pp.344-345
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    • 2018
  • In order to alleviate the negative impacts of harmonically distorted grid condition on grid-connect inverters, an optimal control design-based gain selection scheme of an LCL-filtered grid-connected inverter and its ability to compensate selective harmonics are presented in this paper. By incorporating resonant terms into the control structure in the state-space to provide infinity gain at selected frequencies, the proposed control offers an excellent steady-state response even under distorted grid voltage. The proposed control scheme is achieved by using a state feedback controller for stabilization purpose and by augmenting the resonant terms as well as intergral term into a control structure for reference tracking and harmonic compensation. Furthermore, the optimal linear quadratic control approach is adopted for choosing an optimal feedback gain to ensure an asymptotic stability of the whole system. A discrete-time full state observer is also introduced into the proposed control scheme for the purpose of reducing a total number of sensors used in the inverter system. The simulation results are given to prove the effectiveness and validity of the proposed control scheme.

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Combined Relay Selection and Cooperative Beamforming for Physical Layer Security

  • Kim, Jun-Su;Ikhlef, Aissa;Schober, Robert
    • Journal of Communications and Networks
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    • v.14 no.4
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    • pp.364-373
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    • 2012
  • In this paper, we propose combined relay selection and cooperative beamforming schemes for physical layer security. Generally, high operational complexity is required for cooperative beamforming withmultiple relays because of the required information exchange and synchronization among the relays. On the other hand, while it is desirable to reduce the number of relays participating in cooperative beamforming because of the associated complexity problem, doing so may degrade the coding gain of cooperative beamforming. Hence, we propose combined relay selection and cooperative beamforming schemes, where only two of the available relays are selected for beamforming and data transmission. The proposed schemes introduce a selection gain which partially compensates for the decrease in coding gain due to limiting the number of participating relays to two. Both the cases where full and only partial channel state information are available for relay selection and cooperative beamforming are considered. Analytical and simulation results for the proposed schemes show improved secrecy capacities compared to existing physical layer security schemes employing cooperative relays.

ModifiedFAST: A New Optimal Feature Subset Selection Algorithm

  • Nagpal, Arpita;Gaur, Deepti
    • Journal of information and communication convergence engineering
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    • v.13 no.2
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    • pp.113-122
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    • 2015
  • Feature subset selection is as a pre-processing step in learning algorithms. In this paper, we propose an efficient algorithm, ModifiedFAST, for feature subset selection. This algorithm is suitable for text datasets, and uses the concept of information gain to remove irrelevant and redundant features. A new optimal value of the threshold for symmetric uncertainty, used to identify relevant features, is found. The thresholds used by previous feature selection algorithms such as FAST, Relief, and CFS were not optimal. It has been proven that the threshold value greatly affects the percentage of selected features and the classification accuracy. A new performance unified metric that combines accuracy and the number of features selected has been proposed and applied in the proposed algorithm. It was experimentally shown that the percentage of selected features obtained by the proposed algorithm was lower than that obtained using existing algorithms in most of the datasets. The effectiveness of our algorithm on the optimal threshold was statistically validated with other algorithms.

Maximizing the Selection Response by Optimal Quantitative Trait Loci Selection and Control of Inbreeding in a Population with Different Lifetimes between Sires and Dams

  • Tang, G.Q.;Li, X.W.;Zhu, L.;Shuai, S.R.;Bai, L.
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.11
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    • pp.1559-1571
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    • 2008
  • A rule was developed to constrain the annual rate of inbreeding to a predefined value in a population with different lifetimes between sires and dams, and to maximize the selection response over generations. This rule considers that the animals in a population should be divided into sex-age classes based on the theory of gene flow, and restricts the increase of average inbreeding coefficient for new offspring by limiting the increase of the mean additive genetic relationship for parents selected. The optimization problem of this rule was formulated as a quadratic programming problem. Inputs for the rule were the BLUP estimated breeding values, the additive genetic relationship matrix of all animals, and the long-term contributions of sex-age classes. Outputs were optimal number and contributions of selected animals. In addition, this rule was combined with the optimization of emphasis given to QTL, and further increased the genetic gain over the planning horizon. Stochastic simulations of closed nucleus schemes for pigs were used to investigate the potential advantages obtained from this rule by combining the standard QTL selection, optimal QTL selection and conventional BLUP selection. Results showed that the predefined rates of inbreeding were actually achieved by this rule in three selection strategies. The rule obtained up to 9.23% extra genetic gain over truncation selection at the same rates of inbreeding. The combination of the extended rule and the optimization of emphasis given to QTL allowed substantial increases in selection response at a fixed annual rate of inbreeding, and solved substantially the conflict between short-term and long-term selection response in QTL-assisted selection schemes.

Design method of computer-generated controller for linear time-periodic systems

  • Jo, Jang-Hyen
    • 제어로봇시스템학회:학술대회논문집
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    • 1992.10b
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    • pp.225-228
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    • 1992
  • The purpose of this project is the presentation of new method for selection of a scalar control of linear time-periodic system. The approach has been proposed by Radziszewski and Zaleski [4] and utilizes the quadratic form of Lyapunov function. The system under consideration is assigned either in closed-loop state or in modal variables as in Calico, Wiesel [1]. The case of scalar control is considered, the gain matrix being assumed to be at worst periodic with the system period T, each element being represented by a Fourier series. As the optimal gain matrix we consider the matrix ensuring the minimum value of the larger real part of the two Poincare exponents of the system. The method, based on two-step optimization procedure, allows to find the approximate optimal gain matrix. At present state of art determination of the gain matrix for this case has been done by systematic numerical search procedure, at each step of which the Floquet solution must be found.

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Study of New Control Method for Linear Periodic System

  • Jo, Janghyen
    • 제어로봇시스템학회:학술대회논문집
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    • 1999.10a
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    • pp.83-87
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    • 1999
  • The purpose of this study is to provide the new method for selection of a close to optimal scalar control of linear time-periodic system. The case of scalar control is considered, the gain matrix being assumed to be at worst periodic with the system period T. The form of gain matrix may have various kinds but must have same period, for example, one of each element being represented by Fourier series. As the optimal gain matrix I consider the matrix ensuring the minimum value of the larger real part of the Poincare exponents of the system. Finally we present a pole placement algorithm to make the given system be stable. It is possible to determine the stability of the given periodic system without get the analytic solution. The application of the method does not require the construction of the Floquet solution. At present state of determination of the gain matrix for this case will be done only by systematic numerical search procedures.

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An enhanced feature selection filter for classification of microarray cancer data

  • Mazumder, Dilwar Hussain;Veilumuthu, Ramachandran
    • ETRI Journal
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    • v.41 no.3
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    • pp.358-370
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    • 2019
  • The main aim of this study is to select the optimal set of genes from microarray cancer datasets that contribute to the prediction of specific cancer types. This study proposes the enhancement of the feature selection filter algorithm based on Joe's normalized mutual information and its use for gene selection. The proposed algorithm is implemented and evaluated on seven benchmark microarray cancer datasets, namely, central nervous system, leukemia (binary), leukemia (3 class), leukemia (4 class), lymphoma, mixed lineage leukemia, and small round blue cell tumor, using five well-known classifiers, including the naive Bayes, radial basis function network, instance-based classifier, decision-based table, and decision tree. An average increase in the prediction accuracy of 5.1% is observed on all seven datasets averaged over all five classifiers. The average reduction in training time is 2.86 seconds. The performance of the proposed method is also compared with those of three other popular mutual information-based feature selection filters, namely, information gain, gain ratio, and symmetric uncertainty. The results are impressive when all five classifiers are used on all the datasets.

Design of unknown input observer of wheelbase preview control of commercial vehicles (상용 차량의 축거 예견 제어를 위한 미지 입력 관측기 설계)

  • 노현석;박영진
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.892-895
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    • 1996
  • An unknown input observer is proposed that can be used in wheelbase preview control of commercial vehicles. The preview and state information, required to calculate actuator force, are reconstructed from the measurement variables such as heave and pitch acceleration. Gain matrix of observer is optimally selected so that influence of system and measurement noises on the estimation error can be minimized. Estimated preview information requires low pass filtering to eliminate high frequency components resulting from differentiation of noisy output signals. Effectiveness of the proposed method is demonstrated by numerical simulation of half car model.

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Exploring an Optimal Feature Selection Method for Effective Opinion Mining Tasks

  • Eo, Kyun Sun;Lee, Kun Chang
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.2
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    • pp.171-177
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    • 2019
  • This paper aims to find the most effective feature selection method for the sake of opinion mining tasks. Basically, opinion mining tasks belong to sentiment analysis, which is to categorize opinions of the online texts into positive and negative from a text mining point of view. By using the five product groups dataset such as apparel, books, DVDs, electronics, and kitchen, TF-IDF and Bag-of-Words(BOW) fare calculated to form the product review feature sets. Next, we applied the feature selection methods to see which method reveals most robust results. The results show that the stacking classifier based on those features out of applying Information Gain feature selection method yields best result.