• Title/Summary/Keyword: Frequency Weighting Function

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Robust PI controller design using LQ-servo (LQ-servo를 이용한 강인한 PI제어기 설계)

  • 이동영;윤성오;서병설
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.577-580
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    • 1996
  • LQ-servo is a stability-robustness guaranteed multivariable controller design method based on the LQR structure to improve command following performance with output feedback. In this paper, a new type of PI controller based on LQ-servo is introduced. Then, Command following performance is improved using the limiting behavior of the control gain and weighting factors on the low frequency part of design parameter Q that is the state weighting matrix in the cost function.

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Wide-band beamforming with gaussian weighting (가우시안 가중치에 의한 광대역 빔형성 특성)

  • 도경철;손경식
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.639-642
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    • 1998
  • This paper proposes a new wide-band beamforming which has guassian weighting. For the prupose of measurement this beam is formed by using all sensors toghether, not octave-by-octave. Weighting is applied to each sensor before time-delay compensation as a frequency-dependent function. As the resutls of the simulation of the proosed algorithm for nested linear array having 17 sensors for each octave, it is confirmed that beam can be formed with all sensors together and uniform directivity index can be achieved by proposed algorithm.

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A Simple Method for Frequency Domain Identification

  • Choe, Yeon-Wook
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.129-134
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    • 1998
  • In this paper, a simple method is presented to synthesize a transfer function from experimentally obtained gain and phase data. The method we offer here is based on the previous method given by M.Hassul etc. [1], where they proposed relevant formulas in a straightforward manner so that undergraduate students could follow the development more easily. This method, however, inevitably is accompanied by a significant difference between the real and identified model especially in the low frequency region. We solve this problem by introducing a new weighting function that can be determined by using the additive uncertainty of the Identified transfer function.

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Directivity Characteristics of Wide-Band One-Shot Beam Formed with Gaussian Weighting (가우시안 가중치에 의한 광대역 단일빔의 지향 특성)

  • 도경철;손경식
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.1
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    • pp.25-31
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    • 1999
  • This paper proposes a new wide-band beamforming algorithm which has Gaussian weighting at nested linear array for acoustic measurement. The beamforming is performed one-shot by using all sensors simultaneously, not octave-by-octave. Gaussian weighting of frequency-dependent function is applied to each sensor before time-delay compensation so as to control the frequency receiving band of each sensor. As the results of the simulations, it is confirmed that the proposed algorithm can form the one-shot beams having uniform directivity index and also it can be applied to the broad-band acoustic measurement.

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Ride Quality Assessment of Automative Seats by Simultaneous 3-Axis Excitation (동시 3축 가진에 의한 자동차 의자류의 승차감 평가)

  • 정완섭;우춘규;박세진;김수현
    • Journal of KSNVE
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    • v.7 no.1
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    • pp.143-152
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    • 1997
  • This paper introduces experimental results of the ride qulaity characteristics of automotive seats fixed on the vibration table that is noving simultaneously to the three-axis in a similar way to the real running condition. Vibration experiment was carried out for five different automotive seats and four Korean individuals. The assessment of the ride quality characteristics for each seat and indiviual was made not only from the analysis of vibration measurements but also from the evaluation of weighied vibration signals, which were obtained using the frequency weighting function and the multiplication factor dependent on the position and axis of vibration exposure to wehole-body. The usefulness of those assessment results in analysis of the ride quality of seats is discussed and their limitation is also pointed out in this paper.

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A new Implementation of Perceptual LPC Cepstrum and its Application to Speech Recognition (인지 LPC cepstrum의 새로운 구현 및 음성인식에의 적용)

  • Kim, Jin-Young;Choi, Seong-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.5
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    • pp.61-64
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    • 1996
  • To improve the performance of a recognition system, namely the recognition rate, we propose a hew implementation of perceptual distance using LPC cepstrum(perceptual cepstrum, PLC). The PLC is caculated by convolution of a usual LPC cepstrum and a perceptual lifter(PL). To caculate PL, we define a new weighting function in the linear frequency domain considering the frequency scale(Bark-scale) characteristics. The PL is the inverse Fourier transform of the exponents of the weighting function. We verified our method through the speech recognition experiments. The performance of PLC was compared with that of the rasied sine liftering method.

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A Calculation Method of Source Level of Underwater Transient Noise by Frequency Band (주파수 대역별 수중 순간소음 음원준위 산출 기법)

  • Choi, Jae-Yong;Oh, Jun-Seok;Lee, Phil-Ho
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.4
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    • pp.528-533
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    • 2010
  • This paper describes a calculation method of source level of a ship transient noise, which is one of the important elements for the ship detection. Aim of transient noise measurements is to evaluate of acoustic energy due to singular occurrence, which is therefore defined as non-periodic and short termed events like an attack periscope, a rudder and a torpedo door. In generally, in the case of randomly spaced impulse, the spectrum becomes a broadband random noise with no distinctive pattern. Therefore, frequency analysis is not particularly revealing for type of signal. In the paper, it is performed in time domain to analyze a transient noise. However, a source level of transient noise is required an investigation for multiple frequency band. So, in order to calculate a source level of transient noise, a design of exponential weighting function, convolution, band pass filtering, peak detection, root mean square, and parameter compensation are applied. The effectiveness of this calculation scheme is studied through computer simulations and a sea test. Furthermore, an application of the method is applied in a real case.

A PCA-based MFDWC Feature Parameter for Speaker Verification System (화자 검증 시스템을 위한 PCA 기반 MFDWC 특징 파라미터)

  • Hahm Seong-Jun;Jung Ho-Youl;Chung Hyun-Yeol
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.1
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    • pp.36-42
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    • 2006
  • A Principal component analysis (PCA)-based Mel-Frequency Discrete Wavelet Coefficients (MFDWC) feature Parameters for speaker verification system is Presented in this Paper In this method, we used the 1st-eigenvector obtained from PCA to calculate the energy of each node of level that was approximated by. met-scale. This eigenvector satisfies the constraint of general weighting function that the squared sum of each component of weighting function is unity and is considered to represent speaker's characteristic closely because the 1st-eigenvector of each speaker is fairly different from the others. For verification. we used Universal Background Model (UBM) approach that compares claimed speaker s model with UBM on frame-level. We performed experiments to test the effectiveness of PCA-based parameter and found that our Proposed Parameters could obtain improved average Performance of $0.80\%$compared to MFCC. $5.14\%$ to LPCC and 6.69 to existing MFDWC.

Mel-Frequency Cepstral Coefficients Using Formants-Based Gaussian Distribution Filterbank (포만트 기반의 가우시안 분포를 가지는 필터뱅크를 이용한 멜-주파수 켑스트럴 계수)

  • Son, Young-Woo;Hong, Jae-Keun
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.8
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    • pp.370-374
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    • 2006
  • Mel-frequency cepstral coefficients are widely used as the feature for speech recognition. In FMCC extraction process. the spectrum. obtained by Fourier transform of input speech signal is divided by met-frequency bands, and each band energy is extracted for the each frequency band. The coefficients are extracted by the discrete cosine transform of the obtained band energy. In this Paper. we calculate the output energy for each bandpass filter by taking the weighting function when applying met-frequency scaled bandpass filter. The weighting function is Gaussian distributed function whose center is at the formant frequency In the experiments, we can see the comparative performance with the standard MFCC in clean condition. and the better Performance in worse condition by the method proposed here.

Localization of Mobile Robot Based on Radio Frequency Identification Devices (RFID를 이용한 이동로봇의 위치인식기술)

  • Lee Hyun-Jeong;Choi Kyu-Cheon;Lee Min-Cheol;Lee Jang-Myung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.1
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    • pp.41-46
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    • 2006
  • Ubiquitous location based services, offer helpful services anytime and anywhere by using real-time location information of objects based on ubiquitous network. Particularly, autonomous mobile robots can be a solution for various applications related to ubiquitous location based services, e.g. in hospitals, for cleaning, at airports or railway stations. However, a meaningful and still unsolved problem for most applications is to develop a robust and cheap positioning system. A typical example of position measurements is dead reckoning that is well known for providing a good short-term accuracy, being inexpensive and allowing very high sampling rates. However, the measurement always has some accumulated errors because the fundamental idea of dead reckoning is the integration of incremental motion information over time. The other hand, a localization system using RFID offers absolute position of robots regardless of elapsed time. We construct an absolute positioning system based on RFID and investigate how localization technique can be enhanced by RFID through experiment to measure the location of a mobile robot. Tags are placed on the floor at 5cm intervals in the shape of square in an arbitrary space and the accuracy of position measurement is investigated . To reduce the error and the variation of error, a weighting function based on Gaussian function is used. Different weighting values are applied to position data of tags since weighting values follow Gaussian function.