• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.629-632
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• 1997

This paper presents the design method of controller which is combined Genetic Algorithms with the Generalized minimum variance self tuning controller. It is shown that the controllers adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a polynomial parameters. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.216-228
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• 1995

Under the certain assumptions, we derive the recursive formula for the predictive probabilities that a new patient will survive up to the time, conditional on the data. The formula for a new patient is extended to obtain the computational algorithms for the predictive probabilties for several new patients. We correct Genest and Kalbfleisch's approach for several new patients, since we find that their approach is incorrect.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.746-750
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• 2001

During the last decades several proposals have been made in literature to use predictive control for inverter control-especially in electrical drives. These algorithms are completely different to the recursive but linear predictive algorithms known from information theory, where closed mathematical equations are used (e.g. Kalman-filters). Only few of the presented schemes have been realized in industrial applications so far. After some further progress, however, the advantage of predictive algorithms might lead to an increased number of industrial implementations in the future. Besides the common basic idea - to use the well-known but strongly non-linear behaviour of inverters to precalculate the best switching times - there are many differences in the details of these proposals. This contribution shows similarities and differences and attempts to design a 'family tree' of predictive control algorithms. This might grow to a first step to a theoretical approach to deal with predictive control schemes in a more generalised way.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1020-1026
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• 2016

Motion estimation (ME) algorithms supporting quarter-pixel accuracy have been recently introduced to retain detailed motion information for high quality of video in the state-of-the-art video compression standard of H.264/AVC. Conventional sub-pixel ME algorithms in the spatial domain are faced with a common problem of computational complexity because of embedded interpolation schemes. This paper proposes a low-complexity sub-pixel motion estimation algorithm in the transform domain utilizing shifting matrix. Simulations are performed to compare the performances of spatial-domain ME algorithms and transform-domain ME algorithms in terms of peak signal-to-noise ratio (PSNR) and the number of bits per frame. Simulation results confirm that the transform-domain approach not only improves the video quality and the compression efficiency, but also remarkably alleviates the computational complexity, compared to the spatial-domain approach.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.101-108
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• 2001

In this study, the static and dynamic characteristics of endmilling process were modelled and the analytic realization of chatter mechanism was discussed. In this reward, We have discussed on the comparative assessment of recursive time series modeling algorithms that cal represent time machining process and detect the abnormal machining behaviors in precision endmilling operation. In this study, simulation and experimental works were performed to show the malfunctional behaviors. For this purpose, new recursive algorithm(RLSM) was adopted for the oil-line system identification and monitoring of a machining process, we can apply these new algorithms in real process for detection of abnormal chatter. Also, The stability lobe of chatter was analysed by varying parameter of cutting dynamics in regenerative chatter mechanics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.

• Journal of the Korea Society of Computer and Information
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• v.26 no.2
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• pp.61-68
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• 2021

Recently, various technologies that use machine learning to classify malicious code have been studied. In order to enhance the effectiveness of machine learning, it is most important to extract properties to identify malicious codes and normal binaries. In this paper, we propose a feature extraction method for use in machine learning using recursive methods. The proposed method selects the final feature using recursive methods for individual features to maximize the performance of machine learning. In detail, we use the method of extracting the best performing features among individual feature at each stage, and then combining the extracted features. We extract features with the proposed method and apply them to machine learning algorithms such as Decision Tree, SVM, Random Forest, and KNN, to validate that machine learning performance improves as the steps continue.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.271-286
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• 2011

In this paper, we propose efficient algorithms for parallel prefix computation and sorting on a recursive dual-net. The recursive dual-net $RDN^k$(B) for k > 0 has $(2n_o)^{2K}/2$ nodes and $d_0$ + k links per node, where $n_0$ and $d_0$ are the number of nod es and the node-degree of the base-network B, respectively. Assume that each node holds one data item, the communication and computation time complexities of the algorithm for parallel prefix computation on $RDN^k$(B), k > 0, are $2^{k+1}-2+2^kT_{comm}(0)$ and $2^{k+1}-2+2^kT_{comp}(0)$, respectively, where $T_{comm}(0)$ and $T_{comp}(0)$ are the communication and computation time complexities of the algorithm for parallel prefix computation on the base-network B, respectively. The algorithm for parallel sorting on $RDN^k$(B) is restricted on B = $Q_m$ where $Q_m$ is an m-cube. Assume that each node holds a single data item, the sorting algorithm runs in $O((m2^k)^2)$ computation steps and $O((km2^k)^2)$ communication steps, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.6
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• pp.609-615
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• 2000

The energy conservation is one of the most important issues in recent years. Especially, the energy conservation through improved control strategies is one of the most highly possible area to be implemented in the near future. The energy conservation of the ice storage system can be accomplished through the improved control strategies. A real time building load prediction algorithm was developed. The expected highest and the lowest outdoor temperature of the next day were used to estimate the next day outdoor temperature profile. The measured dry bulb temperature and the measured building load were used to estimate system parameters by using the on-line weighted recursive least square method. The estimated hourly outdoor temperatures and the estimated hourly system parameters were used to predict the next day hourly building loads. In order to see the effectiveness of the building load prediction algorithm, two different types of building models were selected and analysed. The simulation results show less than 1% in error for the prediction of the next day building loads. Therefore, this algorithm may successfully be used for the development of improved control algorithms of the ice storage system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.10
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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.