• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.540-547
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• 2004

Since speech enhancement algorithms based on Kalman/Wiener filter require a priori knowledge of the noise and have focused on the minimization of the variance of the estimation error between clean and estimated speech signal, small estimation error on the noise statistics may lead to large estimation error. However, H/sub ∞/ filter does not require any assumptions and a priori knowledge of the noise statistics, but searches the best estimated signal among the entire estimated signal by applying least upper bound, consequently it is more robust to the variation of noise statistics than Kalman/Wiener filter. In this paper, we Propose a speech enhancement method using HMM and multi H/sub ∞/ filters. First, HMM parameters are estimated with the training data. Secondly, speech is filtered with multiple number of H/sub ∞/ filters. Finally, the estimation of clean speech is obtained from the sum of the weighted filtered outputs. Experimental results shows about 1dB∼2dB SNR improvement with a slight increment of computation compared with the Kalman filter method.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.71-79
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• 1997

In this paper, a codeword-dependent distance normalization(CDDN) and an instar-formed fuzzy smoothing of output distribution are proposed for robust estimation of output probabilities in the FVQ(fuzzy vector quantization)-DHMM(discrete hidden Markov model). The FVQ-DHMM is a variant of DHMM in which the state output probability is estimated by the sum oft he product of the output probability and its weighting factor for each codeword on an input vector. As the performance of the FVQ-DHMM is influenced by weighting factor and output distribution from a state, it is required to get a method to get robust estimation of weighting factors and output distribution for each state. From experimental results, the proposed CDDN method has reduced 24% of error rate over the conventional FVQ-DHMM, and also reduced 79% of error rate when the smoothing of output distribution is also applied to the computation of an output probability. These results indicate that the use of CDDN and the fuzzy smoothing of output distribution to the FVQ-DHMM lead to improved recognition, and therefore it may be used as an alternative to the robust estimation of output probabilities for HMMs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.416-422
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• 2017

The robot control with safety consideration is required since robots and human work together in the same space more frequently in these days. For safety, robots must have compliance to human force and robust tracking performance with high impednace for the nonhuman disturbances. The novel idea is proposed to achieve the compliance and high impedance with one controller structure. For the compliance, the ISMC(Integral Sliding Mode Control) and HDOB(Human Disturbance Observer) The human force is identified by using the human band pass filter and its output is sent to the sliding surface. The sliding mode dynamic is affected by human disturbance and the compliance for human is achieved. The disturbances besides human frequencies are decoupled by the ISMC and the robust tracking is achieved. The additional LDOB(Low Frequency Disturbance Observer) decreases the maxim nonlinear gain and leads low chattering. The introduction of human disturbance into the sliding mode dynamic is the main novel idea of this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.13-25
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• 2011

Biometric-based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as the compromise of the data will be permanent. The fuzzy fingerprint vault system is one of the most popular solutions for protecting the fingerprint template stored in the database. Recently, however, this system is very susceptible to a correlation attack that finds the real minutiae using multiple fingerprint vaults enrolled for different applications. To solve this problem, we propose a robust fuzzy fingerprint vault system against the correlation attack. In this paper, we add chaff minutiae based on the relative information of minutiae such as direction, coordinate instead of adding randomly. Also, our proposed approach allow to add multiple chaff minutiae within tolerance box for enhanced security level. Experimental results show that the proposed approach can protect the correlation attack and achieve enhanced verification accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.1
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• pp.59-65
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• 2005

This paper proposes a novel TSK fuzzy modeling algorithm. Various approaches to fuzzy modeling when noise or outliers exist in the data have been presented but they are approaches to degrade effects of outliers or large noise by using loss function in the cost function mainly. The proposed algorithm is the modified version of noise clustering algorithm, and it adopts the method that does not use loss function, but method to cluster noise in a class. Noise clustering is a prototype-based clustering algorithm and it has no capability to regress. It conducts clustering of data first, and then conducts fuzzy regression. There are many algorithms to obtain parameters of premise and consequent part simultaneously, but they need to adapt the parameters obtained for more accurate approximation. In this paper, fuzzy regression is conducted with clustering by modifying noise clustering algorithm. We propose the algorithm that parameters of the premise part and the consequent part are obtained simultaneously, and the parameters obtained are not needed to adapt. We verify the proposed algorithm through simple examples and evaluate the test results compared with existing algorithms. The proposed algorithm shows robust performance against noise and it is easy to implement.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.50-59
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• 2011

In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.64-74
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• 2014

The primary and ambient signal decomposition of a stereo sound is a key step to the stereo upmix. The principal component analysis (PCA) is one of the most widely used methods of primary-ambient signal decomposition. However, previous PCA-based decomposition algorithms assume that stereo sound sources are only amplitude-panned without any consideration of phase difference. So it occurs some performance degradation in case of live recorded stereo sound. In this paper, we propose a new PCA-based stereo decomposition algorithm that can consider the phase difference between the channel signals. The proposed algorithm overcomes limitation of conventional signal model using PCA with phase alignment. The phase alignment is realized by using inter-channel phase difference (IPD) which is widely used in parametric stereo coding. Moreover, Enhanced Modified PCA(EMPCA) is combined to solve the problem of conventional PCA caused by Primary to Ambient energy Ratio(PAR) and panning angle dependency. The simulation results are presented to show the improvements of the proposed algorithm.

• Journal of Advanced Navigation Technology
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• v.19 no.2
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• pp.123-132
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• 2015

Among various fields of the CNS/ATM, the surveillance field which includes ADS-B system, MLAT system, and WAM system is implemented. These next generation systems provide superior performance in tracking aircrafts. However, They still have error. In this paper, filtering algorithm is proposed in order to enhance aircraft tracking performance of ADS-B, MLAT, and WAM systems. The proposed method is a Robust Interacting Multiple Model filter, called Robust IMM filter, that improves IMM filter. The Robust IMM filter can not only improves the aircraft tracking performance but also track aircraft continually using estimates calculated from the filter when data losses occur. The simulation results of the proposed aircraft tracking methods show that the filtering data provides a better performance up to an average of 19.21%.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.53-54
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• 2008

플랜트의 모델 없이 주파수 응답만으로 안정도와 여러 성능(이득여유, 위상여유, $H_{\infty}$ 여유)을 만족하는 1차 보상기 설계 이론이 최근에 발표되었다[1]. 그중 안정도를 만족하는 제어기의 셋을 구하는 것의 수치해를 [6]에서 제시하였고, 본 논문에서는 그것을 확장하여 여러 성능을 동시에 만족하는 셋을 구하는 알고리즘을 제시하고 그것을 이용한 MATLAB용 설계 도구를 소개한다.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.239-242
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• 2001

영상에 워터마크를 삽입하는 것을 통신채널의 입장에서 해석한다면 워터마크는 신호로, 영상은 잡음으로 모델링이 가능하다. 따라서 이러한 잡음 속에서 신호에 대한 에러를 최소화하는 것이 워터마크의 추출을 최대화하는 것이라 할 수 있다. 통상적으로 Error Correction Code는 에러가 많은 통신채널에서 많이 이용되기 때문에 워터마킹 방법에서도 효과를 기대할 수 있다. 본 논문에서는 DCT 기반의 구간화 워터마킹 방법에 Turbo code를 이용하여 강인성 면에서의 향상된 성능을 실험 결과로 보이며, Turbo code의 해밍거리를 이용하여 워터마킹의 보다 효율적인 검출 방법을 제안한다.