• The Journal of the Acoustical Society of Korea
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• v.19 no.6
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• pp.53-61
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• 2000

In the speech recognition under the noisy environments, reducing the mismatch introduced between training and testing environments is an important issue. Spectral subtraction is widely used technique because of its simplicity and relatively good performance in noisy environments. In this paper, we introduce histogram method as a reliable noise estimation approach for spectral subtraction. This method has advantages over the conventional noise estimation methods in that it does not need to detect non-speech intervals and it can estimate the noise spectra even in time-varying noise environments. Even though spectral subtraction is performed using a reliable average noise spectrum by the histogram method, considerable amount of residual noise remains due to the variations of instantaneous noise spectrum about mean. To overcome this limitation, we propose a new over-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 has advantages to be few the influence of the SNR variation on the noise levels. According to speaker-independent isolated word recognition experiments in car noise environment under various SNR conditions, the proposed histogram-based over-estimation technique outperforms the conventional over-estimation technique.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.08a
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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.

• Proceedings of the IEEK Conference
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• 2006.06a
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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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.7
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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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• v.5 no.2
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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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• v.29 no.1
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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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• 1994.02b
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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.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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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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• v.6 no.9
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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.

• Journal of IKEEE
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• v.27 no.4
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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.