• 한국음향학회지
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• 제19권6호
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• pp.53-61
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• 2000

잡음환경에서의 음성인식 성능향상을 위해서는 서로 다른 잡음환경으로 인한 mismatch를 줄이는 것이 중요하다. 이를 위해 계산이 간단하고 잡음환경에서 비교적 우수한 성능을 내고 있는 스펙트럼 차감법이 널리 사용되고 있다. 본 논문에서는 스펙트럼 차감법을 적용하기 위한 잡음 스펙트럼 추정방법으로 히스토그램 처리방법을 도입한다. 히스토그램 처리방법은 음성이 아닌 구간의 검출이 필요없으며 시간에 따라 변화하는 시변잡음에도 적용 가능한 장점이 있다. 그러나 히스토그램 처리방법으로 신뢰도 높은 잡음 스펙트럼의 평균값을 추정하더라도 스펙트럼 차감법을 적용했을 때의 잔여 잡음의 문제가 발생한다. 이를 해결하기 위하여 잡음추정 과정에 사용되었던 히스토그램의 분포특성을 고려한 새로운 over-estimation 적용방식을 제안한다. 제안된 방식은 측정된 잡음의 분포에 따라 적응적으로 over-estimation의 정도를 결정함으로써 SNR 변화에 따른 영향이 적은 장점이 있다. 자동차 소음 환경에서의 화자독립 고립단어 인식실험 결과, 기존의 over-estimation factor를 적용한 경우보다 제안된 방식의 인식성능이 개선되었다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 제15회 음성통신 및 신호처리 워크샵(KSCSP 98 15권1호)
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• pp.262-266
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• 1998

In the speech recognition under the noisy environments, reducing the mismatch introduced between training and testing environments is an important issue, and spectral subtraction is widely used technique because of its simplicity and relatively good performance in noisy environments. In this paper, we introduced histogram method as a reliable noise estimationi approach for spectral subtraction. To deal with the problem of residual noise after spectral subtraction, we proposed a new ove-estimation technique based on distribution characteristics of histogram used for noise estimation. Since the proposed technique decides the degree of over-estimation adaptively according to the measured noise distribution, it can cope with the SNR variations effectively in compared with the conventional over-estimation technique.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.17-18
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• 2006

In this paper, we propose a robust detection scheme of OSTBCs with channel estimation errors over time-selective fading channels. Channel estimation errors are inevitable over time-selective fading channels and even small channel estimation errors dramatically degrade the performance of space-time block coding schemes. Therefore, it is desired to investigate the effect of channel estimation errors on the performance of the proposed detection scheme compared with the existing detection scheme. The proposed detection scheme minimizes noise enhancement and impact of channel estimation errors which occur in an existing detection scheme. It is shown by simulations that the proposed detection scheme performs better than the existing detection scheme over time-selective fading channels.

• 조명전기설비학회논문지
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• 제29권7호
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• pp.38-46
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• 2015

This paper propose a variable parameter estimations for variable over current load of five-phase squirrel-cage induction motor(IM) to servo control system. In order to high performance control of AC motor using a field oriented control(FOC) and direct torque control(DTC) algorithm, there are required precise motor parameters for slip calculation, flux observer, controller gain, torque command of current components, rotor position, speed estimation, and so on. We are suggest a analyzed estimation results of the motor parameters that developing five-phase squirrel-cage IM have a stator of concentrated winding for experimental within variable over current load at rated input frequency. There are results of stator winding measurement, no-load test, locked-rotor test, variable over current load test, and estimated parameters of equivalent circuits using manufactured experimental apparatus by IEEE Standard Test Procedure for Polyphase Induction Motors and Generators 112-2004.

• Journal of Communications and Networks
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• 제5권2호
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• pp.167-173
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• 2003

We treat the problem of channel estimation and interference cancellation in multiuser ultra-wide-band (UWB) communication systems over multipath fading channels. The UWB system under consideration employs a random time-hopping impulse radio format. We develop a channel estimation method based on linear weighted algorithm. An iterative channel estimation and interference cancellation scheme is proposed to successively improve the receiver performance. We also consider systems employing multiple transmit and/or receive antennas. For systems with multiple receive antennas, we develop a diversity receiver for the wellseparated antennas. For systems with multiple transmit antennas, we propose to make use of Alamouti’s space-time transmission scheme, and develop the corresponding channel estimation and interference cancellation receiver techniques. Simulation results are provided to demonstrate the performance of various UWB receiver techniques developed in this paper.

• ETRI Journal
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• 제29권1호
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• pp.110-112
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• 2007

As an alternative to the classic linear detector which only assumes noise variance, a new robust detector with noise variance estimation censoring input signals over AWGN is proposed. The results demonstrate that analytic detection probability matches the simulation results for the linear detector and that the new robust detector shows better performance than the linear detector when the number of samples increases.

• 대한예방의학회:학술대회논문집
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• 대한예방의학회 1994년도 교수 연수회(역학)
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• pp.297-312
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• 1994

Over the last decade, considerable interest has focused on sample size estimation in the design of clinical trials. The resulting literature is scattered over many textbooks and journals. This paper presents these methods in a single review and comments on their application in practice.

• 한국자동차공학회논문집
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• 제23권6호
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• pp.633-641
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• 2015

The ROM (roll over mitigation) system is a next-generation suspension system that can improve vehicle-driving stability and ride comfort. Currently, mass-produced safety systems, such as ESC (electronic stability control) and ECS (electronic control suspension), enable measurements of longitudinal and lateral acceleration as well as yaw rate through inertial sensor clusters, but they lack direct measurements of the roll angle. Therefore, in this paper, a roll angle estimation algorithm from ESC system sensors and tire normal force has been proposed. Furthermore, this study presents a method for roll over mitigation force distribution between the front and rear of a ROM system. Performance and reliability of the roll angle estimation and roll over mitigation force distribution were investigated through simulations. The simulation results showed that the proposed control algorithm and strategy are reliable during vehicle rollovers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2218-2230
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• 2012

In this paper, we propose an efficient channel delay estimation method for orthogonal frequency-division multiplexing (OFDM) systems, especially over doubly-selective fading channels which are selective in both the symbol time domain and subcarrier frequency domain. For the doubly-selective fading channels in single frequency network (SFN), long and strong echoes exist and thus the conventional discrete Fourier Transform (DFT) based channel delay estimation system often fails to produce the exact channel delay profile. Based on the analysis of the discrete-time frequency response of the channel impulse response (CIR) coefficients in the DFT-based channel delay estimation system, we develop a method to effectively extract the true CIR from the aliased signals by employing a simple narrow-band low-pass filter (NB-LPF). The performance of the proposed system is verified using the COST207 TU6 SFN channel model.

• 전기전자학회논문지
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• 제27권4호
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• pp.430-438
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• 2023

The Modular Multilevel Converter (MMC) has emerged as a key component in HVDC systems due to its ability to efficiently transmit large amounts of power over long distances. In such systems, accurate estimation of the MMC capacitor voltage is of utmost importance for ensuring optimal system performance, stability, and reliability. Traditional methods for voltage estimation may face limitations in accuracy and robustness, prompting the need for innovative approaches. In this paper, we propose a novel distributed neural network observer specifically designed for MMC capacitor voltage estimation. Our observer harnesses the power of a multi-layer neural network architecture, which enables the observer to learn and adapt to the complex dynamics of the MMC system. By utilizing a distributed approach, we deploy multiple observers, each with its own set of neural network layers, to collectively estimate the capacitor voltage. This distributed configuration enhances the accuracy and robustness of the voltage estimation process. A crucial aspect of our observer's performance lies in the meticulous initialization of random weights within the neural network. This initialization process ensures that the observer starts with a solid foundation for efficient learning and accurate voltage estimation. The observer iteratively updates its weights based on the observed voltage and current values, continuously improving its estimation accuracy over time. The validity of proposed algorithm is verified by the result of estimated voltage at each observer in capacitor of MMC.