• Journal of the Korea Safety Management & Science
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• v.14 no.1
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• pp.155-165
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• 2012

This essay talks about research of robust design for quality improvement of production procedure of Wet Etchant. It suggested the optimum design method in consideration of specific capability value that is the way to maximize the quality of product in the production system by using Daguchi parameter design method while finding factors affecting product quality with analysis of production system of product A from producer D. Also, it set long term of 6months as noise factor and let it to be the robust design that can find the optimum condition of control factor that is dull to the changes of each month, that is the change in noise factor. The control factor which affects the product quality is decided as combination method, temperature of raw material, combination time and as there are too many possibilities for combination methods, we performed 4 methods first based on previous research data then derived three ways with product that passed SPEC and set as the factor. As a result of application of optimum production procedure suggested in this essay to the actual production process with its standardization, there was a effect of drop of more than 10particles in comparison to the particle number of previous product and also it brought the effect that resulted the stable number of particle of under 30 that is what the client company suggested.

• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.179-187
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• 2012

This paper presents a novel method for estimating reliable noise spectral magnitude for acoustic background noise suppression where only a single microphone recording is available. The proposed method finds noise estimates from spectral magnitudes measured at line spectral frequencies (LSFs), under the observation that adjacent LSFs are near the peak frequencies and isolated LSFs are close to the relatively flattened valleys of LPC spectra. The parameters used in the proposed method are LPC coefficients, their corresponding LSFs, and the gain of LPC residual signals, so it suits well to LPC-based speech coders.

• Proceedings of the KSPS conference
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• 2002.11a
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• pp.179-182
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• 2002

The development of noise robust speech processing systems is becoming increasingly important as speech technology is currently widely applied in real world applications. Recently, to resolve such a noise problem, adaptive noise canceller(ANC) is frequently used, which is based upon adaptive filters. The adaptive recursive filters perform better than adaptive non-recursive filters due to the added poles, but the stability may be severely threatened. But these problems of adaptive recursive filters was solved by ACHARF algorithm. This paper presents a method which combines speaker verification system with ANC(Adaptive Noise Canceller) using the ACHARF algorithm. In the front-end stage, ANC is adopted to suppress the additive noise imposed on the speech signal. The results show that the performance of speaker verification system becomes better than before.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.127-130
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• 2007

The conventional feature recombination technique is very effective in the band-limited noise condition, but in broad-band noise condition, the conventional feature recombination technique does not produce notable performance improvement compared with the full-band system. To cope with this drawback, we introduce a new technique of sub-band likelihood computation in the feature recombination, and propose a new feature recombination method by using this sub-band likelihood computation. Furthermore, the reliable sub-band selection based on the signal-to-noise ratio is used to improve the performance of this proposed feature recombination. Experimental results shows that the average error reduction rate in various noise condition is more than 27% compared with the conventional full-band speaker identification system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.20-33
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• 2015

Spectrum sensing is a key component of cognitive radio. The prediction of the primary user status in a low signal-to-noise ratio is an important factor in spectrum sensing. However, because of noise uncertainty, secondary users have difficulty distinguishing between the primary signal and an unauthorized signal when an unauthorized user exists in a cognitive radio network. To resolve the sensitivity to the noise uncertainty problem, we propose an entropy-based spectrum sensing scheme to detect the primary signal accurately in the presence of an unauthorized signal. The proposed spectrum sensing uses the conditional entropy between the primary signal and the unauthorized signal. The ability to detect the primary signal is thus robust against noise uncertainty, which leads to superior sensing performance in a low signal-to-noise ratio. Simulation results show that the proposed spectrum sensing scheme outperforms the conventional entropy-based spectrum sensing schemes in terms of the primary user detection probability.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1340-1345
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• 2010

FRC(Frame Rate Control) has been applied to the monitor and TV product as part of cost-saving in many flat panel display manufacturers. As FRC can represent the same number of gray scale level with bits of a smaller amount than bits of the input image data, it is widely used. However, FRC causes visual artifacts by using repeatedly pre-designed the FRC unit size of block pattern in display devices. Therefore, this paper analyzes the cause of the visual artifacts. And in order to improve them, it proposed the pattern arrangement of FRC unit blocks through frame rolling method as analytic solution for the first time. So, we could embody causes of FRC noise. Using the proposed structure, more robust pattern to FRC noise will be designed.

• ETRI Journal
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• v.35 no.4
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• pp.644-654
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• 2013

In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Economic and Environmental Geology
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• v.38 no.2 s.171
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• pp.155-163
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• 2005

For an unbiased TF (Tansfer Function) estimations we investigate geomagnetic TF derived from ICHEON and YONGIN sites, employing RR (Remote Reference) and SNS (Signal Noise Separation) techniques. The Rh technique, which requires synchronized field variations recorded at a clean remote site, is a reliable method to minimize the bias of TF by uncorrelated noises in magnetic channels. Meanwhile, SNS technique based on the assumption of noise-free remote data can improve the signal-noise level by separating signal TF and noise TF, which is successfully applied to the environments with strong correlated noises. In this study, TF at YONGIN is analyzed using geomagnetic data from ICHEON site as a remote reference, which seem to have somewhat better data quality. The application of Rh technique reduces the bias of TF, which appears in single site robust estimation, and makes curves in the amplitude and phase of TF more smooth as frequency. Futhermore, in order to investigate noise source quantitatively, SNS technique is applied. The results of SNS suggest that dominant noise source seems to be located at western region of YONGIN. This noise source is considered to originate from railway system such as KTX and national subway. which passes through the west regions of YONGIN.