• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.371-376
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• 1994

This paper presents an on-line modeling method approach for the machine condition. the machine condition is continuously monitored with a sensor such as, a vibration, a current, an acoustic emission (AE) sensor. In this study, neural network modeling by radial basis function is designed for analysis a prediction error. An on-line learning algorithm is designed using the RLS(recursive least square) estimation and the existing clustering method of Kohonen neural network. Experimental results show that the proposed RBNN modeling is suitable for predicting simulated data.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(1)
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• pp.65-68
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• 2002

본 논문은 HomePNA 2.0 시스템에서 채널에 의한 왜곡을 보상하기 위한 방안을 제시하는 것으로서 심벌률과 전송 방식에 따른 등화기를 Fast RLS 알고리즘인 FTF (Fast Transversal Filter) 알고리즘을 사용하여 구현하여 그 성능을 분석하며, 또한 헤더 부분의 미결정 심벌들을 이용하는 DFE (Decision Feedback Equalizer)형태로 등화기를 구성하고 이에 대한 성능을 분석하고자한다.

• 한국인터넷방송통신학회논문지
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• 제18권3호
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• pp.215-221
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• 2018

본 논문에서는 캡슐 내시경을 위한 HBC(Human Body Communication) 시스템의 종합적인 설계 방법을 제시하였다. 먼저 환자 몸에 부착된 다수의 패치로부터 수신되는 신호를 차동 연산을 통해 합성하는 방법을 제시하고 이를 통한 신호 SNR을 수학적으로 유도하였다. 캡슐에서 보내는 HBC 송신신호를 동기화하기 위한 방법으로 PN 코드를 이용한 대략적 타이밍 동기 방법과 ZCD(Zero Crossing Detector)를 통한 Manchester, NRZ, RZ 변조 기법간의 미세 타이밍 동기 성능을 분석하였다. 아울러 HBC 신호 프레임을 Rician 및 Rayleigh 채널 환경에서 적용하였을 때의 등화 성능을 LMS 및 RLS 알고리즘을 적용하여 평가하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권7호
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• 전자공학회논문지B
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• 제32B권10호
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• pp.1326-1337
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• 1995

In this paper, we transformed the bilinear filter into an equivalent linear multichannel filter and derived QR decomposition based recursive least squares algorithms for bilinear lattice filters. We also defined order update relation of the forward and the backward input vectors by using the channel decomposition. The forward and the backward data matrices were defined by using the forward and the backward input vectors and orthogonalized with the QR decomposition. we can obtain the lattice equations of the bilinear filters by using the channel decomposition. we can be derived the lattice equations of the bilinear filters using this decomposition process which are the same as the lattice equations derived by Baik, we can use the coefficient transformation algorithm proposed by Baik. We derived the equation error and the output error algorithm of the QRD based RLS bilinear lattice algorithm. Also, we evaluated the performance of the proposed algorithms through the system identification of the bilinear system.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1992년도 학술논문발표회 논문집 제11권 1호
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• pp.76-80
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• 1992

We consider the tapped-delay line (TDL) equalizer with the few calculation quantity and the simplity, the decision feedback equalizer (DFE) with the good property for interference, and lattice equalizer(LE) with high insensitivity to roundoff noise in mobile communication fading channel. The used adaptive algorithm is the LMS algorithm and RLS algorithm. In this paper, we have evaluated the performance of the TDL equalizer, the decision feedback equalizer, and lattice-structured equalizer, for the digital signal corrupted by the impulsive noise and the white gaussian noise under the fading channel environment. From the results of error performance analysis, it is confirmed that lattice-structured equalizer has better performance than DFE equalizer and TDL equalizer.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.984-990
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• 2013

This paper develops a new Intelligent Electronic Device (IED), and then presents an application method of a monthly load forecasting algorithm on the smart IEDs. A Multiple Linear Regression (MLR) model implemented with Recursive Least Square (RLS) estimation is established in the algorithm. Case Study proves the accuracy and reliability of this algorithm and demonstrates the practical meanings through designed screens. The application method shows the general way to make use of IED's smart characteristics and thereby reveals a broad prospect of smart function realization in application.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.803-805
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• 2000

In this paper, we propose fuzzy-neural Networks(FNN) which is useful for identification algorithms. The proposed FNN model consists of two steps: the first step, which determines premise and consequent parameters approximately using FCM_RI method, the second step, which adjusts the premise and consequent parameters more precisely by gradient descent algorithm. The FCM_RI algorithm consists FCM clustering algorithm and Recursive least squared(RLS) method, this divides the input space more efficiently than convention methods by taking into consideration correlations between components of sample data. To evaluate the performance of the proposed FNN model, we use the time series data for gas furnace.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.327-331
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• 1989

This paper concerned about a study on the direct pole placement PID self-tuning controller design for Robot manipulator control system. The method of a direct pole placement self-tuning PID control for a DC motor of robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of controller are estimated by the recursive least square(RLS) identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC motor speed control for Robot manipulator by a microcomputer IRH-PC/AT are performed and the results are well suited.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.234-236
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• 2006

Because of its long measurement range and ultra-precise resolution. the heterodyne laser interferometer systems are very common in various industry area such as semiconductor manufacturing. However the periodical nonlinearity property caused from frequency mixing is an obstacle to improve the high measurement accuracy in nanometer scale. In this paper to minimize the effect of nonlinearity, we propose an adaptive nonlinearity compensation algorithm. We first compute compensation parameters using least square (LS) with the capacitance displacement sensor as a reference input. We then update the parameters with recursive LS (RLS) while the values are optimized to modify the elliptical phase into circular one. Through comparison with some experimental results of laser system, we demonstrate the effectiveness of our proposed algorithm.