• 한국음향학회지
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• 제18권8호
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• pp.48-53
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• 1999

본 논문에서는 Sliding-DFT(sliding discrete Fourier transform : SDFT)를 순환구조로 구현할 때 복소수 계수를 유한한 비트로 근사 표현하여 생기는 오차영향을 해석적으로 구하는 방법을 제시하고 유도 과정을 기술하였다. 해석한 결과는 오차전력과 신호전력 비(noise-to-signal power ratio : NSR)의 식으로 얻었으며, DFT 대상신호가 평균이 ‘0’인 가우스 백색신호(zero-mean white Gaussian signal)인 것으로 가정하였다. NSR 식은 복소수계수를 표현하는 비트 수와 DFT 구간길이에 대한 식으로 구하였다. 유도 과정은 SDFF 순환 식(recursive equation)으로 유도한 오차방정식(error dynamic equation)과 계수근 사오차의 공간적인 확률분포특성에 근거하였다. 해석적으로 유도한 NSR 결과를 시뮬레이션 실험을 통해 얻은 결과와 비교하여 타당성을 확인하였다.

• 조명전기설비학회논문지
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• 제22권1호
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• pp.118-123
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• 2008

본 논문은 주파수영역에서 첨두공진점을 갖는 고차모델을 저차모델로 근사화하기 위한 주파수 전달함수 합성법을 제안한다. 제안된 근사화 방법은 근사화된 모델의 분모 다항식에 가중된 오차함수의 최소화에 근거하며, 근사화된 모델의 주파수 전달함수에 대한 계수벡터를 추정하기 위해 RLS 기법을 이용한다. 제안된 방법은 저주파수와 첨두공진점에서 우수한 정합특성을 나타내며, 예제에 의해 제안된 방식의 유용성을 검증한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (B)
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• pp.151-153
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• 2005

오늘날 HTML을 대체하기 위해 등장한 XML은 디지털 정보교환 형식의 표준으로 자리 잡은 후 XML 문서를 데이터베이스에 저장하고 원하는 정보를 효율적으로 질의한 후 결과를 출력하는 연구가 활발히 진행되고 있다. 본 논문에서는 XML 문서를 미리 설계되어진 Analyzer를 이용해서 관계형 테이블에 저장한 후 사용자가 XQuery를 사용하여 질의를 한다. 변환기에 의해서 SQL로 데이터베이스에 질의를 하게 되고 그 결과는 테이블에서 다시 XML 형태로 재생성하여 사용자는 XML 형태의 결과를 볼 수 있다. 본 논문에서는 XQuery로 질의한 결과를 다시 XML로 재생성하는 기법에 대한 설명과 관련 테이블의 구조와 구현 과정을 비롯하여 접기서 제시한 재생성 기법을 recursive function으로 구현한 경우와 반복문으로 구현한 경우를 테스트하여 recursive function으로 구현한 경우가 반복문으로 구현한 경우보다 재생성하는 시간이 빠르다는 것을 확인하고 보다 효율적이라는 결론을 제시한다.

• 제어로봇시스템학회논문지
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• 제8권10호
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• pp.827-832
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• 2002

We propose a prediction method of the pollutant and a synchronous classification of the current state of SOx emission in the power plant. We use the auto-regressive with exogeneous (ARX) model as a predictor of SOx emission and use a radial basis function network (RBFN) as a pattem classifier. The ARX modeling scheme is implemented using recursive least squares (RLS) method to update the model parameters adaptively. The capability of SOx emission monitoring is utilized with the application of the RBFN classifier. Experimental results show that the ARX model can predict the SOx emission concentration well and ARX modeling parameters can be a good feature for the state monitoring. in addition, its validity has been verified through the power spectrum analysis. Consequently, the RBFN classifier in combination with ARX model is shown to be quite adequate for monitoring the state of SOx emission.

• Journal of the Korean Statistical Society
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• 제26권2호
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• pp.277-288
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• 1997

For the analysis of survival data including covariates whose effects vary in time, the multiprocess discount survival model is proposed. The parameter vector modeling the time-varying effects of covariates is to vary between time intervals and its evolution between time intervals depends on the perturbation of the next time interval. The recursive estimation of the parameter vector can be obtained at the end of each time interval. The retrospective estimation of the survival function and the forecasting of the survival function of individuals of the specific covariates also can be obtained based on the information gathered until the end of the time interval.

• 정보처리학회논문지A
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• 제14A권4호
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• pp.245-248
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• 2007

이 논문은 셀의 두 가지 상태값(0,1)과 서로 다른 네가지 경계조건(0-0,0-1,1-0,1-1)하에서, 3근방 국소 천이함수를 갖는 유한오토마타의 천이함수를 생성하는 간단한 재귀적인 공식을 만들어, 이 공식으로 천이 함수를 몇 개의 클래스로 분류한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.965-969
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• 1993

In this paper, the GPC algorithm is developed for ACS(advanced control system). ACS equals to DCS(distributed control system) with some advanced control algorithm, for example, fuzzy logic controller, autotuning. By its embedded structural control language, which uses simple function codes corresponding to each function blocks, it is possible to construct multiloop controller. The developed GPC function code is divided by RLS (recursive least square) parameter estimator and GPC controller. Simulation result show the availability of GPC function code using the control language.

• Bulletin of the Korean Chemical Society
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• 제33권4호
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• pp.1123-1127
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• 2012

P-gp (P-glycoprotein) is a member of the ATP binding cassette (ABC) family of transporters. It transports many kinds of anticancer drugs out of the cell. It plays a major role as a cause of multidrug resistance (MDR). MDR function may be a cause of the failure of chemotherapy in cancer and influence pharmacokinetic properties of many drugs. Hence classification of candidate drugs as substrates or nonsubstrate of the P-gp is important in drug development. Therefore to identify whether a compound is a P-gp substrate or not, in silico method is promising. Recursive Partitioning (RP) method was explored for prediction of P-gp substrate. A set of 261 compounds, including 146 substrates and 115 nonsubstrates of P-gp, was used to training and validation. Using molecular descriptors that we can interpret their own meaning, we have established two models for prediction of P-gp substrates. In the first model, we chose only 6 descriptors which have simple physical meaning. In the training set, the overall predictability of our model is 78.95%. In case of test set, overall predictability is 69.23%. Second model with 2D and 3D descriptors shows a little better predictability (overall predictability of training set is 79.29%, test set is 79.37%), the second model with 2D and 3D descriptors shows better discriminating power than first model with only 2D descriptors. This approach will be used to reduce the number of compounds required to be run in the P-gp efflux assay.

• 자동차안전학회지
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• 제12권4호
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• 무역학회지
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• 제46권6호
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• pp.191-209
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• 2021

In this paper, various time series analysis models and machine learning models are presented for long-term prediction of export growth rate, and the prediction performance is compared and reviewed by RMSE and MAE. Export growth rate is one of the major economic indicators to evaluate the economic status. And It is also used to predict economic forecast. The export growth rate may have a negative (-) value as well as a positive (+) value. Therefore, Instead of using the ReLU function, which is often used for time series prediction of deep learning models, the PReLU function, which can have a negative (-) value as an output value, was used as the activation function of deep learning models. The time series prediction performance of each model for three types of data was compared and reviewed. The forecast data of long-term prediction of export growth rate was deduced by three forecast methods such as a fixed forecast method, a recursive forecast method and a rolling forecast method. As a result of the forecast, the traditional time series analysis model, ARDL, showed excellent performance, but as the time period of learning data increases, the performance of machine learning models including LSTM was relatively improved.