• 한국통신학회논문지
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• 제28권5A호
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• pp.333-340
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• 2003

본 논문에서는 주파수 선택적 페이딩 환경에서도 터보부호화된 모든 정보심벌들이 수신단에서 동일한 신뢰도를 갖도록 전송함으로써, 터보부호화된 OFDM (orthogonal frequency division multiplexing) 시스템의 성능을 크게 향상시키는 새로운 전송 방식을 제안한다. 모든 정보심벌들이 동일한 신뢰도를 갖는다는 것은 페이딩의 영향을 동일하게 받는다는 것을 의미한다. 이를 위하여 각 정보심벌에 서로 다른 직교코드를 할당하여 다중화하고, 이를 전송 가능한 모든 부채널들로 확산시켜 전송한다 (이후, 이 과정은 직교코드 다중화 (orthogonal code multiplexing: OCM) 라고 한다.). 다중화를 위한 직교코드로는 코드의 길이에 상관없이 코드들 상호간의 직교성을 유지하며 코드간 동일한 에너지를 갖는 DFT (discrete Fourier transform) 기본 시퀀스 (basis sequence)를 사용한다. 모의실험을 통하여 제안된 시스템의 성능분석이 이루어지며, 반복 복호를 위해서는 Log-MAP(Log-maximum a posteriori) 알고리즘을 사용한다.

• Composites Research
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• 제16권1호
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• pp.26-33
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• 2003

열-음향방출(thermo-acoustic emission)기법을 이용함으로써, 직교형 복합재료적층판의 저온냉각 시에 형성되는 미세손상을 검출하고 평가하여 그 유효성을 검토하였다. 액체질소에 의한 저온냉각($-191^{\circ}C$)으로 생성된 미세손상은 가열-냉각 열부하사이클 시에 발생하는 음향방출(AE)거동의 해석을 통해 평가되었다. 저온냉각에 따른 섬유파단과 모재파손은 초음파 C스캔, 광학현미경, 주사형 전자현미경을 통해 관찰되었으며, 이들 미세파손 모드는 AE신호의 퓨리에 변환(FFT)처리해석, 단시간 퓨리에 변환(STFT)처리해석으로 분류되는 3종류의 서로 다른 특징을 갖는 AE신호로 검출될 수 있었다. 이들 AE신호특성을 시간 단계별로 검출하여 저온냉각시에 형성되는 복합재료 미세파괴의 과정을 실시간으로 평가할 수 있었으며, 또한 열부하 사이클시의 AE신호해석을 통해서 저온 냉각으로 생성된 미세파손의 정도를 추정할 수 있었다.

• Structural Engineering and Mechanics
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• 제29권2호
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• pp.135-154
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• 2008

The moving vehicle loads on a bridge deck is one of the most important live loads of bridges. They should be understood, monitored and controlled before the bridge design as well as when the bridge is open for traffic. A MOM-based algorithm (MOMA) is proposed for identifying the timevarying moving vehicle loads from the responses of bridge deck in this paper. It aims at an acceptable solution to the ill-conditioning problem that often exists in the inverse problem of moving force identification. The moving vehicle loads are described as a combination of whole basis functions, such as orthogonal Legendre polynomials or Fourier series, and further estimated by solving the new system equations developed with the basis functions. A number of responses have been combined, some numerical simulations on single axle, two axle and multiple-axle loads, being either constant or timevarying, have been carried out and compared with the existing time domain method (TDM) in this paper. The illustrated results show that the MOMA has higher identification accuracy and robust noise immunity as well as producing an acceptable solution to ill-conditioning cases to some extent when it is used to identify the moving force from bridge responses.

• 한국인터넷방송통신학회논문지
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• 제23권6호
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• pp.33-39
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• 2023

최근 비행 애드-훅 네트워크(Flying Ad-hoc Network) 환경에서 강화학습을 이용한 통신 성능 개선과 이동성 모델 설계에 관한 연구가 진행되고 있다. 무인항공기(UAV)에서의 이동성 모델은 움직임을 예측하고 제어하기 위한 핵심요소로 주목받고 있다. 본 논문에서는 무인항공기가 운용되는 3차원 가상 환경을 구현하고, 무인항공기의 경로 최적화를 위해 푸리에 기저 함수 근사를 적용한 Q-learning과 DQN 두 가지 강화학습 알고리즘을 적용하여 모델을 설계 및 성능을 분석하였다. 실험 결과를 통해 3차원 가상 환경에서 DQN 모델이 Q-learning 모델 대비 최적의 경로 탐색에 적합한 것을 확인하였다.

• 전기학회논문지
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• 제58권12호
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• pp.2520-2528
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• 2009

In this paper, we proposed tracking detection methodology using information granulation-based fuzzy radial basis function neural networks (IG-FRBFNN). According to IEC 60112, tracking device is manufactured and utilized for experiment. We consider 12 features that can be used to decide whether tracking phenomenon happened or not. These features are considered by signal processing methods such as filtering, Fast Fourier Transform(FFT) and Wavelet. Such some effective features are used as the inputs of the IG-FRBFNN, the tracking phenomenon is confirmed by using the IG-FRBFNN. The learning of the premise and the consequent part of rules in the IG-FRBFNN is carried out by Fuzzy C-Means (FCM) clustering algorithm and weighted least squares method (WLSE), respectively. Also, Hierarchical Fair Competition-based Parallel Genetic Algorithm (HFC-PGA) is exploited to optimize the IG-FRBFNN. Effective features to be selected and the number of fuzzy rules, the order of polynomial of fuzzy rules, the fuzzification coefficient used in FCM are optimized by the HFC-PGA. Tracking inference engine is implemented by using the LabVIEW and loaded into embedded system. We show the superb performance and feasibility of the tracking detection system through some experiments.

• 천문학회지
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• 제37권5호
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• pp.349-353
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• 2004

Magnetic fields are an important ingredient of galaxy clusters and are indirectly observed on cluster scales as radio haloes and radio relics. One promising method to shed light on the properties of cluster wide magnetic fields is the analysis of Faraday rotation maps of extended extragalactic radio sources. We developed a Fourier analysis for such Faraday rotation maps in order to determine the magnetic power spectra of cluster fields. In an advanced step, here we apply a Bayesian maximum likelihood method to the RM map of the north lobe of Hydra A on the basis of our Fourier analysis and derive the power spectrum of the cluster magnetic field. For Hydra A, we measure a spectral index of -5/3 over at least one order of magnitude implying Kolmogorov type turbulence. We find a dominant scale of about 3 kpc on which the magnetic power is concentrated, since the magnetic autocorrelation length is ${\lambda}_B = 3 {\pm} 0.5\;kpc$. Furthermore, we investigate the influences of the assumption about the sampling volume (described by a window function) on the magnetic power spectrum. The central magnetic field strength was determined to be ${\~}7{\pm}2{\mu}G$ for the most likely geometries.

• 조명전기설비학회논문지
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• 제24권8호
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• pp.84-93
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• 2010

이 논문은 이산신호가 연속적으로 입력될 때, 이산신호에서 고속으로 파라미터를 추정하고, 그 결과를 시각화하는 방법에 대해서 기술하고 있다. 이 논문은 이산푸리에변환에서 직접 파라미터를 추정하는 고속파라미터 추정 알고리즘을 적용하여 연속신호에서 파라미터를 추정하고, 추정한 중요 파라미터들을 효율적으로 시각화하는 방법에 대해서 기술하고 있다. 이 논문에서 제안한 연속신호에 대한 저주파 파라미터 추정방법을 3개의 모드를 가진 시험함수에 적용하여 제안한 알고리즘과 시각화의 효율성을 검증하였다.

• Journal of Power Electronics
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• 제14권3호
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• pp.564-571
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• 2014

Rotor initial position is an important factor affecting the control performance of electrically excited synchronous motors. This study presents a novel method for estimating rotor initial position based on sliding discrete Fourier transform (sDFT). By injecting an ac excitation into the rotor winding, an induced voltage is generated in stator windings. Through this voltage, the stator flux can be obtained using a pure integral voltage model. Considering the influence from a dc bias and an integral initial value, we adopt the sDFT to extract the fundamental flux component. A quadrant identification model is designed to realize the accurate estimation of the rotor initial position. The sDFT and high-pass filter, DFT, are compared in detail, and the contrast between dc excitation and ac injection is determined. Simulation and experimental results verify that this type of novel method can eliminate the influence of dc bias and other adverse factors, as well as provide a basis for the control of motor drives.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.1060-1071
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• 2014

Signals of the Electroencephalogram (EEG) can reflect the electrical background activity of the brain generated by the cerebral cortex nerve cells. This has been the mostly utilized signal, which helps in effective analysis of brain functions by supervised learning methods. In this paper, an approach for improving the accuracy of EEG signal classification is presented to detect epileptic seizures. Moreover, Independent Component Analysis (ICA) is incorporated as a preprocessing step and Short Time Fourier Transform (STFT) is used for denoising the signal adequately. Feature extraction of EEG signals is accomplished on the basis of three parameters namely, Standard Deviation, Correlation Dimension and Lyapunov Exponents. The Artificial Neural Network (ANN) is trained by incorporating Levenberg-Marquardt(LM) training algorithm into the backpropagation algorithm that results in high classification accuracy. Experimental results reveal that the methodology will improve the clinical service of the EEG recording and also provide better decision making in epileptic seizure detection than the existing techniques. The proposed EEG signal classification using feed forward Backpropagation Neural Network performs better than to the EEG signal classification using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier in terms of accuracy, sensitivity, and specificity.

• Bulletin of the Korean Chemical Society
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• 제10권2호
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• pp.123-128
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• 1989

Calorimetric study in conjunction with Fourier-transform infrared (FTIR) spectroscopic study was carried out on the blends of poly(ethylene oxide) (PEO) with isotactic, atactic and syndiotactic poly(methyl methacrylate) (i-, a-, and s-PMMA). From the differential scanning calorimetric (DSC) measurements, the three types of blends show a depression of the melting temperatures. This indicates that PEO is compatible with i-, a-, and s-PMMA. But the largest melting point depressions of PEO are always found in the blends with s-PMMA. For PEO/a-PMMA and PEO/s-PMMA, the degree of crystallinity as a function of composition deviates substantially from that of the ideal blend in which no interaction between the components exists. The FTIR spectra of all three types of blends are recorded. In order to observe the microstructural changes of PEO in blends, we analyzed the spectra using digital weighted subtraction and addition techniques. It was concluded that the microstructures of PEO are strongly perturbed by the PMMA's. Among these blends PEO microstructure in PEO/s-PMMA blends is most greatly influenced. It indicates that the blending is most preferred with s-PMMA than a- and i-PMMA. It can be explained on the basis of the molecular structure of PMMA's.