• Title/Summary/Keyword: time-varying signals

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Study on Be-Dopplerization Technique for Rotating Source Localization (마이크로폰 어레이를 이용한 회전하는 소음원 가시화에 관한 연구)

  • Park, Sung;Lee, Ja-Hyung;Choi, Jong-Soo;Kim, Jai-Moo;Rhee, Wook
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2005.11a
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    • pp.200-204
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    • 2005
  • The use of beamforming method and de-Dopplerization technique was applied in studying the rotating sound sources. Acoustic analysis of a moving sound source required that the measured sound signals be do-Dopplerized and restored as of the original emission signals. Two main issues of the signal reconstruction in time domain are addressed herein: First, to remove Doppler effect from the measured data and to restore the original emission data of the moving source. The difference of the time domain beamforming from the frequency domain beamforming was mentioned. Also, the time domain beamforming method is deployed in the test and the comparisons were made to the frequency domain results. The time domain signal reconstruction was numerically simulated prior to the application. To validate the de-Dopplerization Performance, the rotating Point sources were examined and localized by the use of a phased array of microphone. The application of prop-rotor was conducted in a hovering condition. The results of reconstructing time signals of rotating sources and its locations were shown in the power distribution maps. In the prop-rotor measurements, the acoustic source locations were successfully verified in varying positions for different frequencies of interest.

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The Selection of the Optimal Gator Wavelet Shape Factor Using the Shannon Entropy Concept (Shannon 엔트로피 개념을 이용한 가보 웨이블렛 최적 형상의 선정)

  • Hong, Jin-Chul;Kim, Yoon-Young
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11b
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    • pp.176-181
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    • 2002
  • The continuous Gabor wavelet transform (GWT) has been utilized as a useful time-frequency analysis tool to identify the rapidly-varying characteristics of some wave signals. In the application of GWT, it is important to select the Gabor wavelet with the optimal shape factor by which the time-frequency distribution of a signal can be accurately estimated. To find the signal-dependent optimal Gabor wavelet shape factor, the notion of the Shannon entropy which mesures the extent of signal energy concentration in the time-frequency plane is employed. To verify the validity of the present entropy-based scheme, we have applied it to the time-frequency analysis of a set of elastic bending wave signals generated by an impact in a solid cylinder.

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Sub-Nyquist Nonuniform Sampling and Perfect Reconstruction of Speech Signals (음성신호의 Sub-Nyquist 비균일 표준화 및 완전 복구에 관한 연구)

  • Lee, He-Young
    • Speech Sciences
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    • v.12 no.2
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    • pp.153-170
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    • 2005
  • The sub-Nyquist nonuniform sampling (SNNS) and the perfect reconstruction (PR) formula are proposed for the development of a systematic method to obtain minimal representation of a speech signal. In the proposed method, the instantaneous sampling frequency (ISF) varies, depending on the least upper boundary of spectral support of a speech signal in time-frequency domain (TFD). The definition of the instantaneous bandwidth (IB), which determines the ISF and is used for generating the set of samples that represent continuous-time signals perfectly, is given. Also, the spectral characteristics of the sampled data generated by the sub-Nyquist nonuniform sampling method is analyzed. The proposed method doesn't generate the redundant samples due to the time-varying property of the instantaneous bandwidth of a speech signal.

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Localization of Rotating Sound Sources Using Beamforming Method (빔 형성 방법을 이용한 회전하는 음원의 위치 판별에 관한 연구)

  • 이재형;홍석호;최종수
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.837-842
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    • 2004
  • The positions of rotating sound sources have been localized by experiments with the Doppler effects removed. In order to do-Dopplerize the sound signals emitted from moving sources, two kinds of signal reconstruction methods were applied. One is the forward propagation method and the other is the backward propagation method. Forward propagation method analyze the source emission time based on the instantaneous distance between sensors and the assumed source position, then the signals are reconstructed with respect to the emission time. On the other hand, the backward method uses time delay to do-Dopplerize the acquired data for the received time of reference. In both techniques, the reconstructed signal data were processed using beamforming algorithm to produce power distributions at the frequency of interest. Experiments have been carried out for varying frequencies, rotating speeds and the object distances. Forward propagation method has shown better performance in locating source position than the backward propagation method.

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A Study on Recognition of the Event-Related Potential in EEG Signals Using Wavelet and Neural Network (웨이브렛과 신경회로망을 이용한 뇌 유발 전위의 인식에 관한 연구)

  • 최완규;나승유;이희영
    • Proceedings of the IEEK Conference
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    • 2000.06e
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    • pp.127-130
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    • 2000
  • Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

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A STUDY ON THE TIME-VARYING POWER SPECTRUM ESTIMATION ALGORITHM USING TIME-FREQUENCY REPRESENTATION (시주파수 표현에 의한 시변파워스펙트럼 추정 알고리즘에 관한 연구)

  • Lee, Jeong-Whan;Lee, Joon-Young;Lee, Dong-Joon;Kim, Han-Soo;Jeon, Woo-Chul;Lee, Myoung-Ho
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.991-993
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    • 1999
  • This study proposed a new algorithm to assess autonomic function activity using Time-Frequency Representation(TFR). TFR is a way of describing the time-valiant energy of a signal. A discrete Wigner representation that is capable of filtering out any cross terms occuring in the Wigner-Ville Distribution(WVD) is used for time-variant energy distribution of heart rate variability(HRV) signals. And the marginal condition are evaluated to estimate power spectrum of HRV signals. The proposed algorithm showed that estimated power spectrum of HRV signals well describe the autonomic nerve system function and also showed the dynamics of autonomic nervous system response.

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A Methodology of Finding the Direction of Lightning Discharge using Loop-type Magnetic Field Sensors (루프형 자계센서를 이용하여 뇌방전이 발생한 방향을 탐지하는 기법)

  • Lee, Bok-Hee;Cho, Chi-Youn;Cho, Sung-Chul
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.10
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    • pp.63-68
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    • 2014
  • This paper deals with a methodology that applies the time-varying magnetic fields produced by the cloud discharges to find the direction of thunderstorm movement. We investigated the basic performance of the magnetic field measurement system composed of multi-turn loop-type sensors, the differential amplifier and active integrator. As a result, the response characteristics of the magnetic field sensor system to sinusoidal signals was excellent. The frequency bandwidth ranges from about 1 kHz to 500 kHz, the response sensitivity was 0.16mV/nT. In addition, we proposed the algorithm that determines the direction of lightning discharges using the comparison of the output signals of right-angled loop-type magnetic field sensors. The accuracy of the direction finding of lightning discharges is fairly well within the measurement error of less than $5^{\circ}$. The magnetic field measurement system proposed in this work can be used to track the direction of thunderstorm movement.

Robust Adaptive Hybrid Control System against Time-varying Periodic Disturbance Signal (시변 주기외란 신호에 대한 강인 적응형 하이브리드 제어시스템)

  • Cho, Hyun-Cheol;Kim, Gwan-Hyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.05a
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    • pp.586-588
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    • 2011
  • Adaptive feedforward control(AFC) is largely aimed for improving control performance of dynamic systems particularly involving periodic disturbance signals in engineering fields. This paper presents a novel hybrid AFC approach for specific systems with multiple disturbances in control input and state variables. The proposed AFC mechanism is hierarchically composed of the conventional AFC and a PID typed auxiliary control law in parallel. The former is generic to decrease periodic disturbance in control actuators and the latter is additionally constructed to overcome control deterioration due to time-varying uncertainty of given systems. We carry out numerical simulation to test reliability of the hybrid AFC system and compare its control performance with a well-known conventional AFC method in terms of time and frequency domains for proving of its superiority.

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An Algebraic Approach to Optimal Control using STWS (STWS를 이용한 최적제어의 대수적 접근에 관한 연구)

  • 오현철;김윤상;안두수
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.5
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    • pp.561-566
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    • 1998
  • This paper presents an algebraic approach to optimal control for time invariant continuous system using STWS(single term Walsh series). In optimal control, it is well known that the design problem with quadratic performance criteria often involves the determination of time-varying feedback gain matrix by solving the matrix nonlinear Riccati equation and of command signal by solving the integral equation, which makes design procedure quite difficult. Therefore, in order to resolve this problem, this paper is introduced to STWS. In this paper, the time-varying feedback gains and command signals are determined by piecewise constant gains which can be easily obtained from algebraic equation using STWS.

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AM-FM Decomposition and Estimation of Instantaneous Frequency and Instantaneous Amplitude of Speech Signals for Natural Human-robot Interaction (자연스런 인간-로봇 상호작용을 위한 음성 신호의 AM-FM 성분 분해 및 순간 주파수와 순간 진폭의 추정에 관한 연구)

  • Lee, He-Young
    • Speech Sciences
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    • v.12 no.4
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    • pp.53-70
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    • 2005
  • A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

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