• Journal of Information Processing Systems
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• v.11 no.3
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• pp.406-420
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• 2015

We present a secure and robust image watermarking scheme that uses combined reversible DWT-DCT-SVD transformations to increase integrity, authentication, and confidentiality. The proposed scheme uses two different kinds of watermarking images: a reversible watermark, $W_1$, which is used for verification (ensuring integrity and authentication aspects); and a second one, $W_2$, which is defined by a logo image that provides confidentiality. Our proposed scheme is shown to be robust, while its performances are evaluated with respect to the peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), normalized cross-correlation (NCC), and running time. The robustness of the scheme is also evaluated against different attacks, including a compression attack and Salt & Pepper attack.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.10
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• pp.104-110
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• 2015

The disturbance observer (DOB) controller has been widely used in various industrial applications since it is capable of achieving robust stability and disturbance rejection. In this paper, we study the effect of Q-filter on disturbance observer controller for Electro-Magnetic suspension (EMS) systems. We consider three Q-filters and analyze their effects on the robust stability against parameter uncertainties due to mass variation. Moreover, we investigate the influence of sensor noise for three Q-filters. According to our study, robust stability improves as the order of Q-filter decreases. On the other hand, the larger the order of Q-filter, the more the effect of sensor noise can be removed.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.3
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• pp.172-179
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• 2003

Linear matrix Inequality based $H_\infty$ robust controller is designed to control the motion of a 4-axis unbalanced rigid asymmetric rotor supported and controlled by two active magnetic bearings in this paper. To this end, the equations of motion of the system are derived via Hamilton's variational principle and transformed to a state-space form for the standard $H_\infty$ control problem. LMI-based controller, which does not require additional assumptions beyond the usual stabilizability and detectability assumptions, is designed based upon the pole place weighting function and loopshaping technique. The obtained results are compared with those reported in the available literature and the efficiency of the proposed LMI-based $H_\infty$ control is revealed.

• Speech Sciences
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• v.15 no.2
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• pp.67-77
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• 2008

In this paper, we implemented a robust speech recognizer using the TMS320VC33 DSP. For this implementation, we had built speech and noise database suitable for the recognizer using spectral subtraction method for noise removal. The recognizer has an explicit structure in aspect that a speech signal is enhanced through spectral subtraction before endpoints detection and feature extraction. This helps make the operation of the recognizer clear and build HMM models which give minimum model-mismatch. Since the recognizer was developed for the purpose of controlling car facilities and voice dialing, it has two recognition engines, speaker independent one for controlling car facilities and speaker dependent one for voice dialing. We adopted a conventional DTW algorithm for the latter and a continuous HMM for the former. Though various off-line recognition test, we made a selection of optimal conditions of several recognition parameters for a resource-limited embedded recognizer, which led to HMM models of the three mixtures per state. The car noise added speech database is enhanced using spectral subtraction before HMM parameter estimation for reducing model-mismatch caused by nonlinear distortion from spectral subtraction. The hardware module developed includes a microcontroller for host interface which processes the protocol between the DSP and a host.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.19-24
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• 2007

In this paper, we propose a tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller consists of the convex set of PID and PI-PD controller. PID-PD controller controls the closed-loop response to be located between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.784-786
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• 1993

Recently, in the industrial applications, the sensorless system is developed, but the sensorless system is required to have robustness for the measurement noise and disturbance. In this paper, for the sensorless system, the method of designing a robust sliding mode observer taking account of the ability of disturbance and noise attenuation is presented. Also, the strategy for the estimation of rotor flux using the sliding mode observer, which is robust to the measurement noise, is described. Robustness are achieved by assigning the pole of the the system during the sliding motion in such a way as to minimize the effects of the disturbances on the rotor flux estimation error. Finally, using worst case desist and LQC(least square error design), the sliding mode absolver is verified by computer simulations.

• MALSORI
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• no.45
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• pp.107-115
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• 2003

An efficient method that compensates the HMM parameters for the noisy speech recognition is proposed. Instead of assuming some analytical approximations as in the PMC, the proposed method directly re-estimates the HMM parameters by the segmental k-means algorithm. The proposed method has shown improved results compared with the conventional PMC method at reduced computational cost.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.548-553
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• 1998

The specific noise level of 18 rotary compressor mufflers were measured and these data were analyzed by the Taguchi robust design method and the neural network. The optimal design value obtained by the neural network generally showed good agreement with that by the Taguchi method. The effects of eight important design variables on the specific noise level were discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.23-30
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• 2011

In the wireless sensor network(WSN), the detection of precise location of sensor nodes is essential for efficiently utilizing the sensing data acquired from sensor nodes. Among various location methods, the received signal strength (RSS) based localization scheme is mostly preferable in many applications since it can be easily implemented without any additional hardware cost. Since the RSS localization method is mainly effected by radio channel between two nodes, outlier data can be included in the received signal strength measurement specially when some obstacles move around the link between nodes. The outlier data can have bad effect on estimating the distance between two nodes such that it can cause location errors. In this paper, we propose a RSS-based localization method using Robust Statistic and Gaussian filter algorithm for enhancing the accuracy of RSS-based localization. In the proposed algorithm, the outlier data can be eliminated from samples by using the Robust Statistics as well as the Gaussian filter such that the accuracy of localization can be achieved. Through simulation, it is shown that the proposed algorithm can increase the accuracy of localization and is more robust to non gaussian noise channels.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.222-228
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• 2010

In this paper, we propose a new approach to noise estimation incorporating spectral deviation with soft decision scheme to enhance the intelligibility of the degraded speech signal in non-stationary noisy environments. Since the conventional noise estimation technique based on soft decision scheme estimates and updates the noise power spectrum using a fixed smoothing parameter which was assumed in stationary noisy environments, it is difficult to obtain the robust estimates of noise power spectrum in non-stationary noisy environments that spectral characteristics of noise signal such as restaurant constantly change. In this paper, once we first classify the stationary noise and non-stationary noise environments based on the analysis of spectral deviation of noise signal, we adaptively estimate and update the noise power spectrum according to the classified noise types. The performances of the proposed algorithm are evaluated by ITU-T P. 862 perceptual evaluation of speech quality (PESQ) under various ambient noise environments and show better performances compared with the conventional method.