• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.3
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• pp.174-181
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• 2018

This study introduces a systematic approach to selecting the internal parameters applied to the equivalent electrical-circuit model (EECM) of a lithium titanium oxide ($Li_4Ti_5O_{12}$; LTO) rechargeable cell. Based on the dynamic characteristic of the cell, a simplified EECM consisting of an open-circuit voltage (OCV), an ohmic resistance, and an RC ladder is fabricated. To select the internal parameters of a simplified EECM, experiments on discharge capacity, OCV, and discharge/charge resistances are performed using hybrid pulse power characterization and direct current internal resistance (DCIR) measurements over the full state-of-charge (SOC) range. The experimental results of the LTO rechargeable cell highlight the importance of correct selection of internal parameters that can reduce EECM errors. This study clearly provides experimental procedures, internal parameters results, and EECM guidelines for adaptive control-based SOC estimation for LTO rechargeable cells.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.92-99
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• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.447-453
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• 2007

In the multipath fading channel, OFDM(Orthogonal Frequency Division Multiplexing)system possess the characteristics of ISI/ICIwith prefix, but a weak point of circuit complexity and PAPR problem. SC-FDE(Single Carrier with Frequency Domain Equalization) performance is similar to OFDM system, but equalizer is complex in frequency domain. In this paper, simple proportional equalizer offer for SC-FDE system, it useful method in the $2GHz{\sim}\;10GHz$ channel model such as indoor, outdoor, SUI. It prove using MATLAB simulation, speed faster then OFDM system, reduce terminal complexity in same test condition.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.9
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• pp.626-634
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• 2000

The paper describes a new and rigorous mathematical model using counter-EMF for the rotor field oriented system with induction motor which uses the estimated speed and rotor flux based on a Model Reference Adaptive System as well as the real-time approach. The estimated speed and rotor flux is used for the speed and flux feedback control. The stability and the convergence of the estimator are improved on the basis of hyperstability theory for non-linear systems. The validity of the proposed method is verified by simulation and also the sensorless control was tested on the propulsion system simulator used for the development of Korean High-Speed Railway Train(KHSRT).

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2432-2434
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2209-2211
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• 2004

Unlike the wavelet neural network, since a mother wavelet layer of the self-recurrent wavelet neural network (SRWNN) is composed of self-feedback neurons, it has the ability to store past information of the wavelet. Therefore we propose the prediction method for the nonlinear chaotic time series model using a SRWNN. The SRWNN model is learned for the modeling of a function such that the inputs arc known values of the time series and the output is the value in the future. The parameters of the network are tuned to minimize the difference between the nonlinear mapping of the chaotic time series and the output of SRWNN using the gradient-descent method for the adaptive backpropagation algorithm. Through the computer simulations, we demonstrate the feasibility and the effectiveness of our method for the prediction of the logistic map and the Mackey-Glass delay-differential equation as a nonlinear chaotic time series.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.675-681
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• 1989

As an adaptive control function generator, the CMAC (Cerebellar Model Arithmetic or Articulated Controller) based learning control has drawn a great attention to realize a rather robust real-time manipulator control under the various uncertainties. There remain, however, inherent problems to be solved in the CMAC application to robot motion control or perception of sensory information. To apply the CMAC to the various unmodeled or modeled systems more efficiently, It is necessary to analyze the effects of the CMAC control parameters an the trained net. Although the CMAC control parameters such as size of the quantizing block, learning gain, input offset, and ranges of input variables play a key role in the learning performance and system memory requirement, these have not been fully investigated yet. These parameters should be determined, of course, considering the shape of the desired function to be trained and learning algorithms applied. In this paper, the interrelation of these parameters with learning performance is investigated under the basic learning schemes presented by authors. Since an analytic approach only seems to be very difficult and even impossible for this purpose, various simulations have been performed with prespecified functions and their results were analyzed. A general step following design guide was set up according to the various simulation results.

• Journal of electromagnetic engineering and science
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• v.9 no.2
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• pp.71-77
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• 2009

OFDM(Orthogonal Frequency Division Multiplexing) signals sutler serious nonlinear distortion in the nonlinear HPA(High Power Amplifier) because of high PAPR(Peak Average Power Ratio). Nonlinear distortion can be improved by a pre-distorter, but this pre-distorter is insufficient when the PAPR is very high in an OPFDM system. In this paper, a DFT(Discrete Fourier Transform) transform technique is introduced for PAPR reduction. It is especially important to consider the memory effect of HPA for more precise predistortion. Therefore, in this paper, we consider two models, the TWTA(Traveling-Wave Tube Amplifier) model of Saleh without a memory effect and the HPA memory polynomial model that has a memory effect. We design a pre-distorter and an adaptive pre-distorter that uses the NLMS(Normalized Least Mean Square) algorithm for the compensation of this nonlinear distortion. Without the consideration of a memory effect, the system performance would be degraded, even if the pre-distorter is used for the compensation of the nonlinear distortion. From the simulation results, we can confirm that the proposed system shows an improvement in performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3041-3063
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• 2018

Community search aims at finding a meaningful community that contains the query node and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. However, most metric-based algorithms tend to include irrelevant subgraphs in the identified community. Apart from the user-defined metric algorithm, how can we search the natural community that the query node belongs to? In this paper, we propose a novel community search algorithm based on the concept of the k-hop and local distance dynamics model, which can naturally capture a community that contains the query node. The basic idea is to envision the nodes that k-hop away from the query node as an adaptive local dynamical system, where each node only interacts with its local topological structure. Relying on a proposed local distance dynamics model, the distances among nodes change over time, where the nodes sharing the same community with the query node tend to gradually move together, while other nodes stay far away from each other. Such interplay eventually leads to a steady distribution of distances, and a meaningful community is naturally found. Extensive experiments show that our community search algorithm has good performance relative to several state-of-the-art algorithms.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.2 s.3
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• pp.13-22
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• 2003

It is recognized that one of the problems for the current 'Traffic Adaptive Control System in Seoul' is the performance at the oversaturated condition. Instead of 'Degree of Saturation' adopted in the current system, the methodology of balancing the queue length was developed and evaluated in this study. This method keeps the balance of queue lengths on the intersections and reduces the overall queue lengths. In addition a traffic signal control model was developed based on the method. This model can reduce not only the queue lengths but also the average delay of vehicles according to the macroscopic and microscopic evaluations.