• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.243-250
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• 2008

The coverage algorithm based on Boustrophedon path has been known to be the most efficient in places without or less obstacles If the map of an environmental area thru SLAM algorithm can be obtainable. However, the efficiency of the coverage algorithm based on Boustrophedon path drops drastically when obstacles are complex. In this paper, we propose and implement a new algorithm, which we call Group-k, that efficiently handles the complex area. The Group-k algorithm groups the obstacles and prioritizes the covering sequences with complex rank of the groups. Implementation-based experiments show about 20% improved performance when applying the nor- algorithm, compared to the Boustrophedon path algorithm.

• Journal of the Semiconductor & Display Technology
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• v.11 no.3
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• pp.57-61
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• 2012

In order to analyze the ECG, it is important to pinpoint the repeat interval of the ECG. In this paper, we present an efficient algorithm for finding the QRS complex on the ECG. We escaped from the conventional methods to go through multiple steps of preprocessing to make ECG easier to find the QRS complex. We selected the candidate peak that has the possibility of the QRS complex in original ECG, and used technique to find the QRS complex among the candidate peak. In this way, we could get similar efficiency to Pan & Tompkins Algorithm that is most representative QRS complex detection algorithm, just used fewer operations than Pan & Tompkins Algorithm.

• Journal of the Korean Statistical Society
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• v.25 no.3
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• pp.359-368
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• 1996

The maximum likelihood estimation is discussed for the NLAR model with Laplacian marginals. Since the explicit form of the estimates cannot be obtained due to the complicated nature of the likelihood function we utilize the automatic computer optimization subroutine using a direct search complex algorithm. The conditional least square estimates are used as initial estimates in maximum likelihood procedures. The results of a simulation study for the maximum likelihood estimates of the NLAR(1) and the NLAR(2) models are presented.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.5
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• pp.48-58
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• 1998

In this paper, we proposed a new algorithm using characteristics of th ereconstructed phase trajectory by topological mapping developed for a real-tiem detection of the QRS complexes of ECG signals. Using fill-factor algorithm and mutual information algorithm which are in genral used to find out the chaotic characteristics of sampled signals, we inferred the proper mapping parameter, time delay, in ECG signals and investigated QRS detection rates with varying time delay in QRS complex detection. And we compared experimental time dealy with the theoretical one. As a result, it shows that the experimental time dealy which is proper in topological mapping from ECG signals is 20ms and theoretical time delays of fill-factor algorithm and mutual information algorithm are 20.+-.0.76ms and 28.+-.3.51ms, respectively. From these results, we could easily infer that the fill-factor algorithm in topological mapping from one-dimensional sampled ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper ECG signals to two-dimensional vectors, is a useful algorithm for the detemination of the proper time delay. Also with the proposed algorithm which is very simple and robust to low-frequency noise as like baseline wandering, we could detect QRS complex in real-time by simplifying preprocessing stages. For the evaluation, we implemented the proposed algorithm in C-language and applied the MIT/BIH arrhythmia database of 48 patients. The proposed algorithm provides a good performance, a 99.58% detection rate.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.7-18
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• 2003

In this paper, a decision feedback recurrent neural network equalizer and a modified real time recurrent learning algorithm are proposed, and an adaptive adjusting of the learning step is also brought forward. Then, a complex case is considered. A decision feedback complex recurrent neural network equalizer and a modified complex real time recurrent learning algorithm are proposed. Moreover, weights of decision feedback recurrent neural network equalizer under burst-interference conditions are analyzed, and two anti-burst-interference algorithms to prevent equalizer from out of working are presented, which are applied to both real and complex cases. The performance of the recurrent neural network equalizer is analyzed based on numerical results.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.173-176
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• 1996

The transient behavior of the complex-LMS adaptive filter is studied when the adaptive filter is operating on a fixed or sweeping complex frequency sine-wave signal. The first-order difference equation is derived for the mean weights and its closed form solution is obtained. The transient response is represented as a function of the eigenvectors and eigenvalues of input correlation matrix. The mean-square error of the algorithm is evaluated as well. An optimal convergence parameter and filter length can be determined for sweeping frequency sine-wave signals as a function of frequency change rate and signal and noise powers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2167-2172
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• 2008

A large scale embedded generator or a micro-grid is usually interconnected to the grid through the dedicated line. Immediately after the removal of the grid supply, it must be disconnected and remain disconnected until the normal grid supplies are restored. This paper proposes an islanding detection algorithm based on complex power at the intertie. Complex power at the intertie delivered to the grid has a value depending on power flow during normal operation. When loss of mains occurs, complex power at the intertie moves to a value depending on the parameters of the dedicated line. The performance of the proposed algorithm was investigated under various operating and fault conditions. The proposed algorithm can detect an islanding operation even if no power is exchanged prior to loss of mains and discriminate the fault condition from islanding.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1243-1257
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• 2019

As current algorithms unable to perform effective fusion processing of unknown complex radar signals lacking database, and the result is unstable, this paper presents a multi-level fusion processing algorithm for complex radar signals based on evidence theory as a solution to this problem. Specifically, the real-time database is initially established, accompanied by similarity model based on parameter type, and then similarity matrix is calculated. D-S evidence theory is subsequently applied to exercise fusion processing on the similarity of parameters concerning each signal and the trust value concerning target framework of each signal in order. The signals are ultimately combined and perfected. The results of simulation experiment reveal that the proposed algorithm can exert favorable effect on the fusion of unknown complex radar signals, with higher efficiency and less time, maintaining stable processing even of considerable samples.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.314-321
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• 2019

The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.5
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• pp.217-225
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• 2005

In a power system, an out-of-step condition causes a variety of risk such as serious damage to system elements, tripping of loads and generators, mal-operation of relays, etc. Therefore, it is very important to detect the out-of-step condition and take a proper measure. Several out-of-step detection methods have been employed in relays until now. Most common method used for an out-of-step detection is based on the transition time through the blocking impedance area in R-X diagram. Also, the R-R dot out-of-step relay, the out-of-step prediction method and the adaptive out-of-step relay using the equal area criterion (EAC) and Global Positioning Satellite (GPS) technology have been developed. This paper presents the out-of-step detection algorithm using the time variation of the complex power. The complex power is calculated and the mechanical power of the generator is estimated by using the electrical power, and then the out-of-step detection algorithm which is based on the complex power and the estimated mechanical power, is presented. This algorithm may detect the instant when the generator angle passes the Unstable Equilibrium Point (UEP). The proposed out-of-step algorithm is verified and tested by using Alternative Transient Program/Electromagnetic Transient Program (ATP/EMTP) MODELS.