• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.28-31
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• 1996

We propose an estimator design method of Stewart platform, which gives the 6DOF, positions and velcities of Stewart platform from the measured cylinder length. The solution of forward kinematics is not solved yet as a useful realtime application tool because of the complexity of the equation with multiple solutions. Hence we suggest an nonlinear estimator for the forward kinematics solution using Luenberger observer with nonlinear error correction term. But the way of residual gain selection of the estimator is not clear, so we suggest an algebraic Riccati equation for gain matrix using Lyapunov method. This algorithm gives the sufficient condition of the stability of error dynamics and can be extended to general nonlinear system.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.768-771
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• 2004

In this paper, we propose a content-based audio genre classification algorithm that automatically classifies the query audio into five genres such as Classic, Hiphop, Jazz, Rock, Speech using digital signal processing approach. From the 20 second query audio file, 54 dimensional feature vectors, including Spectral Centroid, Rolloff, Flux, LPC, MFCC, is extracted from each query audio. For the classification algorithm, k-NN, Gaussian, GMM classifier is used. In order to choose optimum features from the 54 dimension feature vectors, SFS (Sequential Forward Selection) method is applied to draw 10 dimension optimum features and these are used for the genre classification algorithm. From the experimental result, we verify the superior performance of the SFS method that provides near $90{\%}$ success rate for the genre classification which means $10{\%}$-$20{\%}$ improvements over the previous methods

• Journal of Sensor Science and Technology
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• v.32 no.5
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• pp.313-319
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• 2023

In this study, we propose a method to improve the accuracy of acoustic odometry using optimal frame interval selection for Fourier-based image registration. The accuracy of acoustic odometry is related to the phase correlation result of image pairs obtained from the forward-looking sonar (FLS). Phase correlation failure is caused by spurious peaks and high-similarity image pairs that can be prevented by optimal frame interval selection. We proposed a method of selecting the optimal frame interval by analyzing the factors affecting phase correlation. Acoustic odometry error was reduced by selecting the optimal frame interval. The proposed method was verified using field data.

• Industrial Engineering and Management Systems
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• v.15 no.1
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• pp.63-76
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• 2016

Multiperiod portfolio selection problem attracts more and more attentions because it is in accordance with the practical investment decision-making problem. However, the existing literature on this field is almost undertaken by regarding security returns as random variables in the framework of probability theory. Different from these works, we assume that security returns are uncertain variables which may be given by the experts, and take absolute deviation as a risk measure in the framework of uncertainty theory. In this paper, a new multiperiod mean absolute deviation uncertain portfolio selection models is presented by taking transaction costs, borrowing constraints and threshold constraints into account, which an optimal investment policy can be generated to help investors not only achieve an optimal return, but also have a good risk control. Threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Based on uncertain theories, the model is converted to a dynamic optimization problem. Because of the transaction costs, the model is a dynamic optimization problem with path dependence. To solve the new model in general cases, the forward dynamic programming method is presented. In addition, a numerical example is also presented to illustrate the modeling idea and the effectiveness of the designed algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.293-296
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• 2003

유전 발현 데이터는 생명체의 특정 조직에서 채취한 샘플을 microarray상에서 측정한 것으로 유전자들의 발현 정도가 수치로 나타난 데이터이다. 일반적으로 정상조직과 이상조직에서 관련 유전자들의 발현 정도는 차이를 보이기 때문에, 유전발현 데이터를 통하여 암을 분류할 수 있다. 하지만 분류에 모든 유전자가 관여하지는 않으므로 관련성 있는 유전자만을 선별해내는 작업인 특징 선택방법이 필요하다. 본 논문에서는 회귀분석의 변수선택방법중 하나인 전진 선택법(forward selection method)을 사용하여 유전자들을 선택하고 분류하는 방법을 제안한다. 실험데이터는 대장암 데이트를 사용하였고, 분류기는 KNN을 사용하였다. 이 방법과 상관계수를 이용한 특징 선택 방법인 피어슨 상관계수와 스피어맨 상관계수방법과 비교해본 결과 전진 선택법에 의한 특징 선택방법이 암의 분류에 있어서 더 효과적인 유전자 선택을 한다는 사실을 확인하였다. 실험결과 90.3%의 높은 인식률을 보였다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.4
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• pp.1-8
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• 2012

This paper presents a method for obtaining an exact average symbol error rate (ASER) of M-ary Phase Shift Keying (MPSK) for opportunistic amplify-and-forward (OAF) relay systems over Rayleigh fading channels. This is based on the relay selection probability when a relay is selected as the best one with respect to the received signal-to-noise ratio. We then derive the modified moment generating function (MGF) for OAF relay systems by taking the given relay selection probability into consideration. Based on the modified MGF, we derive the exact ASER which accurately explicates OAF relay system characteristics. Our results confirm that the derived ASER provides a tight upper bound for OAF relay systems.

• Communications for Statistical Applications and Methods
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• v.5 no.1
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• pp.25-33
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• 1998

We review a multivariate version of Kendall's tau based on direction vectors of observations. And with this statistic we propose an analog of the forward variable selection method which selects a set of independent variables for further studies to build the eventual predicting model. This method does not assume the distributions of observations and the linear model and it is strong to the outliers with high asymptotic efficiencies relative to the parametric Pearson's correlation coefficient.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.466-471
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• 2006

IAn important problem of pattern recognition is to extract or select feature set, which is included in the pre-processing stage. In order to extract feature set, Principal component analysis has been usually used and SFS(Sequential Forward Selection) and SBS(Sequential Backward Selection) have been used as a feature selection method. This paper applies genetic algorithm which is a popular method for nonlinear optimization problem to the feature selection problem. So, we call it Genetic Algorithm Feature Selection(GAFS) and this algorithm is compared to other methods in the performance aspect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1016-1033
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• 2016

In this paper, we present a joint relay-and-antenna selection and power allocation strategy for multiple-input multi-output (MIMO) amplify-and-forward (AF) two-way relay networks (TWRNs). In our approach, we select the best transmit and receive antennas at the two sources, a best relay and a best transmit and receive antenna at the selected relay based on maximizing the minimum of the end-to-end received signal-to-noise-ratios (SNRs) under a total transmit power constraints. We obtained the closed-form solution for the optimal power allocation firstly. Then with the optimal allocation solution we found, we can reduce the joint relay-and-antenna selection to a simpler problem. Besides, the overall outage probability is investigated and a tight closed-form approximation is derived, which provides a method to evaluate the outage performance easily and fast. Simulation results are presented to verify the analysis.

• Journal of the Korean Society for Precision Engineering
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• v.2 no.2
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• pp.31-42
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• 1985

The metal flow and the strain distribution is investigated for the steady state and non-steady state bulk deformation processes by using an improved visioplasticity method which includes the effective smoothing scheme. The comparison of various smoothing schemes leads to the selection of the five- point least square smoothing method which is employed to reduce the measurement errors. As a steady state forming process experiments are carried out for axisy- mmetric forward extrusion through conical and curved dies of various area reduc- tions using Aluminum and steel billets. Axisymmetric backward extrusion is chosen for a nonsteady state forming process. In axisymmetric forward extrusion the results from visioplasticity show that the curved die of a fourth-order polynomial renders more uniform distribution of strain rates and strains. Higher reduction leads to greater strain rates at the outer side of the billet. The visioplastic observation for axisymmetric backward extrusion as a non-steady state deformation process shows the concentration of higher strain at the inner wall of the extruded product. The visioplastic results in forward extrusion are in agreement with the computed results by the finite element method. It is thus shown that the visio- plasticity combined with a smoothing technique is an effective method to determine the pattern and the distribution of strain rates and strains.