• Title/Summary/Keyword: FFT method

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A Study on the Crustal Structure Between Pohang, Kongju and Manripo by Gravity Method (중력 탐사에 의한 포항-공주-만리포간의 지각구조 연구)

  • 민경덕
    • Economic and Environmental Geology
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    • v.33 no.2
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    • pp.101-109
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    • 2000
  • The gravity measurement has been carried out to study the deep geologic structure at 331 gravity stations with an interval of 1∼1.5 km along the national road which crosses the southern part of the Korean peninsula from Pohang to Manripo. The Bouguer gravity anomalies were obtained from the observed gravity values, and interpreted by means of upward continuation using FFT (Fast Fourier Transform), Fourier-series method and nonlinear 2-D inversion method to determine the depths of Conrad and Moho discontinuities. The linear regression relations between elevations and gravity anomalies were also obtained to test isostasy in the study area. The depth of Conrad discontinuty is 13km between Pohang and Daegu, 16.5 km between Kimchon and Okchon, 9.7 km between Okchon and Daejeon, and 16.3 km near Manripo. The depth of Moho discontinuty is 32km between Pohang and Daegu, 35 km between Kimchon and Okchon, 28.7 km between Okchon and Daejeon, 40.5 km between Daejeon and Kongju, and 34.5 km between Kongju and Manripo. The result of testing isotasy indicates that the crust of this area seems to be not in perfect isostatic equilibrium but in a little undercompensated sate.

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A New Design Method of Machine Control Interface by Using Bio-signals (생체신호를 이용한 새로운 형태의 기계 제어 인터페이스 구현방법)

  • Jin Kyung-Soo;Park Byoung-Woo;Byeon Jong-Gil
    • The Journal of the Korea Contents Association
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    • v.5 no.1
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    • pp.19-26
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    • 2005
  • This paper introduces a new design method of realizing the machine control interface by using bio-signals(EEG/EOG). This method can be further expanded to be applied to the computer system responding to EEG or EOG signals and the general bio-feedback system. For this reason, we made the remotely controlled toy system controlled by the EEG spectrums, their combination indexes, and EOG parameters. And the headset that has bio-signal processing modules built-in offers convenience for users, and this make much more advanced system than any other existing BCI and BMI system.

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A Novel Compensation Scheme for I/Q Mismatch in an OFDM Direct-Conversion Architecture (OFDM 전송방식 기반의 Direct-Conversion 수신기에서 I/Q 불균형 보상을 위한 새로운 방법 제안)

  • Bae, Jung-Hwa;Park, Jin-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.12C
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    • pp.1265-1272
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    • 2006
  • This paper proposes a compensation method that can alleviate the problem of I/Q mismatch generated in the direct-conversion receiver of OFDM systems. In the proposed method, the amount of I/Q mismatch is estimated using null-carriers in transmitted signals, and it is subtracted from received symbols to suppress I/Q mismatch effects. Simulations show experiments that the proposed method can effectively eliminate the I/Q mismatch effects.

A Study on Training Data Selection Method for EEG Emotion Analysis using Semi-supervised Learning Algorithm (준 지도학습 알고리즘을 이용한 뇌파 감정 분석을 위한 학습데이터 선택 방법에 관한 연구)

  • Yun, Jong-Seob;Kim, Jin Heon
    • Journal of IKEEE
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    • v.22 no.3
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    • pp.816-821
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    • 2018
  • Recently, machine learning algorithms based on artificial neural networks started to be used widely as classifiers in the field of EEG research for emotion analysis and disease diagnosis. When a machine learning model is used to classify EEG data, if training data is composed of only data having similar characteristics, classification performance may be deteriorated when applied to data of another group. In this paper, we propose a method to construct training data set by selecting several groups of data using semi-supervised learning algorithm to improve these problems. We then compared the performance of the two models by training the model with a training data set consisting of data with similar characteristics to the training data set constructed using the proposed method.

Large Eddy Simulation for a 2-D hydrofoil using VIC(Vortex-In-Cell) method (VIC 방법을 사용한 2차원 날개의 LES 해석)

  • Kim, M.S.;Kim, Y.C.;Suh, J.C.
    • 한국전산유체공학회:학술대회논문집
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    • 2011.05a
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    • pp.407-413
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    • 2011
  • VIC (Vortex-In-Cell) method for viscous incompressible flow is presented to simulate the wake behind a modified NACA16 foil. With uniform rectangular grid, the velocity in field is calculated using streamfunction from vorticity field by solving the Poisson equation in which FFT(Fast Fourier Transform) is combined with 2nd order finite difference scheme. Here, LES(Large Eddy Simulation) with Smagorinsky model is applied for turbulence calculation. Effective viscosity is formulated using magnitude of strain tensor(or vorticity). Then the turbulent diffusion as well as viscous diffusion becomes particle strength exchange(PSE) with averaged eddy viscosity. The well-established panel method is combined to obtain the irrotational velocity and to apply the no-penetration boundary condition on the body panel. And wall diffusion is used for no-slip condition numerical results of turbulent stresses are compared with experimental results (Bourgoyne, 2003). Before comparing process, LES(Large Eddy Simulation) SGS(Subgrid scale) stress is transformed Reynolds averaged stress (Winckelmans, 2001).

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Real-Time Physical Activity Recognition Using Tri-axis Accelerometer of Smart Phone (스마트 폰의 3축 가속도 센서를 이용한 실시간 물리적 동작 인식 기법)

  • Yang, Hye Kyung;Yong, H.S.
    • Journal of Korea Multimedia Society
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    • v.17 no.4
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    • pp.506-513
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    • 2014
  • In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.

A Multiresolution Wavelet Scattering Analysis of Microstrip Patch antennas (마이크로스트립 패치 안테나의 다중 분해능 웨이블릿 산란해석법)

  • 강병용;주세훈;빈영부;김형훈;김형동
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.9 no.5
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    • pp.640-647
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    • 1998
  • Microstrip patch antennas are analyzed by a multiresolution wavelet method. The spectral Green's dyad of the structure is obtained and its joint spatial-spectral domain representations are presented. Based on the joint spatial-spectral domain representation, we show that the spectral-domain wavelets are useful in the analysis of this problem. We obtain the matrix equations of the integral equations of this Green's dyad by using the method of moment(MoM), and efficiently solve the problem using the spectral domain wavelet transform concepts in conjuction with the conjugate gradient method. The results for a single-layered square patch are compared with those of conventional MoM and CG-FFT.

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Implementation of Variable Threshold Dual Rate ADPCM Speech CODEC Considering the Background Noise (배경잡음을 고려한 가변임계값 Dual Rate ADPCM 음성 CODEC 구현)

  • Yang, Jae-Seok;Han, Kyong-Ho
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3166-3168
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    • 2000
  • This paper proposed variable threshold dual rate ADPCM coding method which is modified from the standard ADPCM of ITU G.726 for speech quality improvement. The speech quality of variable threshold dual rate ADPCM is better than single rate ADPCM at noisy environment without increasing the complexity by using ZCR(Zero Crossing Rate). In this case, ZCR is used to divide input signal samples into two categories(noisy & speech). The samples with higher ZCR is categorized as the noisy region and the samples with lower ZCR is categorized as the speech region. Noisy region uses higher threshold value to be compressed by 16Kbps for reduced bit rates and the speech region uses lower threshold value to be compressed by 40Kbps for improved speech quality. Comparing with the conventional ADPCM, which adapts the fixed coding rate. the proposed variable threshold dual rate ADPCM coding method improves noise character without increasing the bit rate. For real time applications, ZCR calculation was considered as a simple method to obtain the background noise information for preprocess of speech analysis such as FFT and the experiment showed that the simple calculation of ZCR can be used without complexity increase. Dual rate ADPCM can decrease the amount of transferred data efficiently without increasing complexity nor reducing speech quality. Therefore result of this paper can be applied for real-time speech application such as the internet phone or VoIP.

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A Feature Vector Extraction Method For the Automatic Classification of Power Quality Disturbances (전력 외란 자동 식별을 위한 특징 벡터 추출 기법)

  • Lee, Chul-Ho;Lee, Jae-Sang;Cho, Kwan-Young;Chung, Ji-Hyun;Nam, Sang-Won
    • Proceedings of the KIEE Conference
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    • 1996.11a
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    • pp.404-406
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    • 1996
  • The objective of this paper is to present a new feature-vector extraction method for the automatic detection and classification of power quality(PQ) disturbances, where FFT, DWT(Discrete Wavelet Transform), and data compression are utilized to extract an appropriate feature vector. In particular, the proposed classifier consists of three parts: i.e., (i) automatic detection of PQ disturbances, where the wavelet transform and signal power estimation method are utilized to detect each disturbance, (ii) feature vector extraction from the detected disturbance, and (iii) automatic classification, where Multi-Layer Perceptron(MLP) is used to classify each disturbance from the corresponding extracted feature vector. To demonstrate the performance and applicability of the proposed classification algorithm, some test results obtained by analyzing 7-class power quality disturbances generated by the EMTP are also provided.

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An Automatic Diagnosis for Rotor Bar Faults using Park's vector Pattern (팍스벡터 패턴을 이용한 회전자 바 고장 자동 진단)

  • Song, Myung-Hyun;Park, Kyu-Nam;Han, Dong-Gi;Yang, Chul-Oh
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.361-363
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    • 2007
  • In this paper, an auto-diagnosis method of rotor bar fault for small induction motor is suggested. Usually FFT of stator currents are given the good results, but to detect the fault, slip is needed for calculating the feature frequency. The slip is varied as the load is changed. So in this paper, some alternative method for estimating the load is suggested. This method is based on the Park's vector pattern. The magnitudes of the feature frequency are compared with the threshhold that is predefined in the bounded range of load. The healthy rotor, single rotor bar fault and double rotor bar fault are tested with no load, 25%, 50%, 75%, and 100% rated load. From 50% to 100% rated load case, the rotor bar faults are detectable using indirect estimation of the load and the comparing the magnitudes of feature frequency. The no load case and under 40% rated load case, rotor fault are un detectable.

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