• Title/Summary/Keyword: 잡음예측

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A Low Phase Noise Design of Voltage Controlled Dielectric Resonator Oscillator and Reliability Analysis (전압제어 유전체 공진 발진기의 저위상잡음 설계 및 신뢰도 분석)

  • Ryu Keun-Kwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.2
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    • pp.408-414
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    • 2005
  • The VCDRO(Voltage Controlled Dielectric Resonate. Oscillator) with low phase noise is designed using nonlinear analysis, and its phase noise characteristics are compared with that of Lesson's equation. The microstripline coupled with dielectric resonator is realized as a high impedance inverter to improve the phase noise performance, and the quality factor of resonator circuit can be transferred to active device with the enhanced the loaded quality factor. The worst case and part stress analyses are achieved to obtain the high reliability of VCDRO and the reliability analysis is accomplished to estimate the probability of operation at the end of life. The developed VCDRO has the oscillating tuning factor of 0.56MHZ1V for the control voltage range of 0-l2V. This VCDRO requires the DC power of 136mW. The phase noise characteristics exhibit good performances of -94.18dBc/Hz (a)10KHz and -116.3dBc/Hz (a)100KHz. And, the output power over 7.33dBm is measured.

PCMM-Based Feature Compensation Method Using Multiple Model to Cope with Time-Varying Noise (시변 잡음에 대처하기 위한 다중 모델을 이용한 PCMM 기반 특징 보상 기법)

  • 김우일;고한석
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.6
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    • pp.473-480
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    • 2004
  • In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.

The Analysis of The Kalman Filter Noise Factor on The Inverted Pendulum (도립진자 모델에서 칼만 필터의 잡음인자 해석)

  • Kim, Hoon-Hak
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.5
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    • pp.13-21
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    • 2010
  • The Optimal results of Kalman Filtering on the Inverted Pendulum System requires an effective factor such as the noise covariance matrix Q, the measurement noise covariance matrix R and the initial error covariance matrix $P_0$. We present a special case where the optimality of the filter is not destroyed and not sensitive to scaling of these covariance matrix because these factors are unknown or are known only approximately in the practical situation. Moreover, the error covariance matrices issued by this method predict errors in the state estimate consistent with the scaled covariance matrices and not the issued state estimates. Various results using the scalar gain $\delta$ are derived to described the relations among the three covariance matrices, Kalman Gain and the error covariance matrices. This paper is described as follows: Section III a brief overview of the Inverted Pendulum system. Section IV deals with the mathematical dynamic model of the system used for the computer simulation. Section V presents a various simulation results using the scalar gain.

Enhancement of SBR for Speech Signal Using Adaptive Noise Floor Level (가변 잡음 레벨을 이용한 음성신호에 대한 SBR 성능 항상 기술)

  • Lee, Se-Won;Oh, Seoung-Jun;Ahn, Chang-Beom;Lee, Tae-Jin;Kang, Kyoung-Ok;Park, Ho-Chong
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.2
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    • pp.148-154
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    • 2009
  • In audio coding, SBR technology synthesizes the high-bands using patched time-frequency information from low-bands and the correction parameters, Since SBR transmits only correction parameters for high-bands, it provides a low-rate coding of high-bands, and is used as a core module of MPEG-4 HE-AAC, SBR was originally designed for audio signal and its performance for speech signal tends to decrease, and the major reason is an excessive noise floor in high-bands which is caused by incorrect tonality computation, In this paper, a new method to determine noise floor level in an adaptive fashion according to the speech characteristics is proposed in order to solve the problem of SBR for speech signal, The proposed method maintains the compatibility with the standard SBR, and the subjective performance evaluation shows that the proposed method improves the SBR performance especially for male speech signal compared with the standard SBR.

Forecast of the Daily Inflow with Artificial Neural Network using Wavelet Transform at Chungju Dam (웨이블렛 변환을 적용한 인공신경망에 의한 충주댐 일유입량 예측)

  • Ryu, Yongjun;Shin, Ju-Young;Nam, Woosung;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.45 no.12
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    • pp.1321-1330
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    • 2012
  • In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

A Wideband High-Speed Frequency Synthesizer Using DDS (DDS를 이용한 광대역 고속 주파수 합성기)

  • Park, Beom-Jun;Park, Dong-Chul
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.25 no.12
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    • pp.1251-1257
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    • 2014
  • In this paper, a 6~13 GHz ultra high speed frequency synthesizer having minimum 30 kHz step size and minimum 500 ns frequency settling time is proposed. In order to obtain fast settling time, fine resolution, and good phase noise performance, wideband output frequencies were synthesized based on DDS(Direct Digital Synthesizer) and analog direct frequency synthesis technology. The phase noise performance of wideband frequency synthesizer was estimated by the superposition theory and its results were compared with measured ones. The measured frequency settling time was below 500 ns, phase noise was below -106 dBc @ 10 kHz at 13 GHz, and frequency accuracy was measured below ${\pm}2kHz$.

Noise Reduction Method Using Randomized Unscented Kalman Filter for RGB+D Camera Sensors (랜덤 무향 칼만 필터를 이용한 RGB+D 카메라 센서의 잡음 보정 기법)

  • Kwon, Oh-Seol
    • Journal of Broadcast Engineering
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    • v.25 no.5
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    • pp.808-811
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    • 2020
  • This paper proposes a method to minimize the error of the Kinect camera sensor by using a random undirected Kalman filter. Kinect cameras, which provide RGB values and depth information, cause nonlinear errors in the sensor, causing problems in various applications such as skeleton detection. Conventional methods have tried to remove errors by using various filtering techniques. However, there is a limit to removing nonlinear noise effectively. Therefore, in this paper, a randomized unscented Kalman filter was applied to predict and update the nonlinear noise characteristics, we next tried to enhance a performance of skeleton detection. The experimental results confirmed that the proposed method is superior to the conventional method in quantitative results and reconstructed images on 3D space.

Performance Analysis of Precoded MIMO MMSE Receivers in Transmit-Correlated Rayleigh Channels (송신 상관된 레일리 채널에서 프리코더를 갖는 MIMO MMSE 수신기의 성능 분석)

  • Kim, Wonsop
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38A no.7
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    • pp.552-559
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    • 2013
  • In this paper, the multiple-input multiple-output (MIMO) system with a precoder is considered in the transmit-correlated Rayleigh channels. We specifically target the MIMO system employing the minimum mean square error receivers. Based on random matrix theory, we first present a direct and generalized formulation for deriving a probability density function (PDF) of the signal-to-interference-plus-noise ratio (SINR). Then, we derive the accurate closed-form SINR PDFs for a small number of transmit and receive antennas. Based on the SINR PDFs, tight closed-form approximations of the symbol error rate (SER) are derived. Our analysis suggests that the SER approximations can be used to accurately estimate the error probabilities or as a useful tool for the system design.

Performance Analysis of Highly Effective Proposed Direction Finding Method (제안된 최적전파 도래방향각 예측기법 실현을 위한 성능분석)

  • Rhee, Ill-Keun
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.1E
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    • pp.88-97
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    • 1995
  • The main purpose of this paper is to show the realizaability of the proposed highly effective direction finiding method which performs extremely well under the circumstances like low signal-to-noise ratio (S/N), very closely located signal sources, and so on. In order to achieve the purpose, the degree to which the proposed method is superior to the MUSIC(multiple signal classification) with respect to the S/N is discussed, and the result is analyzed in terms of the S/N and the number of sample data.

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Base plane adaptive filtering for inter plane prediction in RGB video coding (RGB 비디오 압축 부호화의 효율 개선을 위한 적응적 기저 색평면 필터링 기법)

  • Choi, Jang-Won;Jeong, Jin-Woo;Kim, Yang-Soo;Choe, Yoon-Sik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2010.07a
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    • pp.294-296
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    • 2010
  • 일반적으로, RGB 영상의 높은 주파수 영역은 잡음으로 인해 색평면 간 서로 낮은 상관도를 가지고 있기 때문에 이러한 고주파수 성분은 색평면 간 예측의 효율을 저하시키는 원인이 된다. 본 논문에서는 RGB 비디오 코딩에서 색평면 간 예측의 효율을 높이기 위해 기저 색평면을 적응적으로 필터링 하는 방법을 제안한다. 색평면 간 상관도에 따라 적응적으로 기저 색평면을 필터링함으로써 색평면 간 예측 성능을 높일 수 있었다. 본 논문에서 제안하는 알고리즘을 통해 우리는 H.264/AVC High 4:4:4 Intra Profile에 비해 평균 14.71%의 비트율 감소와 0.93dB의 PSNR 향상 결과를 얻을 수 있었다.

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