• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.115-120
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• 2004

This paper concerns the active aeroelastic control of flapped wing systems exposed to blast and/or the sonic boom in an incompressible flow field. This is achieved via implementation of a robust estimation capability (sliding mode observer: SMO), and of the use of the deflected flap as to suppress the flutter instability or enhance the subcritical aeroelastic response to blast loads. To this end, a control methodology using LQG(Linear Quadratic Gaussian) in conjunction with SMO is implemented, and its performance toward suppressing flutter and reducing the vibrational level in the subcritical flight speed range is demonstrated. Moreover, its performances are compared to the ones provided via implementation of conventional LQG with Kalman filter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.438-444
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• 1997

Recently, optical disk drives are increasingly demanded to have higher speed as well as high information density, especially for applications like CD-ROM drives. To this end, improvement of their optical pick-up structure and control is recognized the very challenging issue. In this paper, the 2-D motion of the pick-up is first analytically modelled to identify the cause and effect of the troublesome cross coupling between auto-focusing and tracking directions. Subsequently, the overall system equations are derived to include the dynamics of the related components in the auto-focusing servo system. While its unmeasurable parameters being estimated by the least square error method, a simple but decent linear model can be obtained within its operating frequency range. To design the high speed and robust positional servo controller, the design specifications are detailed and H$\sub$.inf./ control method is employed based on the simple model. Using the pickup in a commercial 8 fold speed CD-ROM drive as an example, performance of the designed controller is verified by realtime experiments.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1606-1613
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• 2021

Recently various attempts to control hardware through integration of sensors and artificial intelligence have been made. This paper proposes a smart hazardous sound detection at home. Previous sound recognition methods have problems due to the processing of background sounds and the low recognition accuracy of high-frequency sounds. To get around these problems, a new MFCC(Mel-Frequency Cepstral Coefficient) algorithm using Wiener filter, modified filterbank is proposed. Experiments for comparing the performance of the proposed method and the original MFCC were conducted. For the classification of feature vectors extracted using the proposed MFCC, DNN(Deep Neural Network) was used. Experimental results showed the superiority of the modified MFCC in comparison to the conventional MFCC in terms of 1% higher training accuracy and 6.6% higher recognition rate.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.252-253
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• 2023

Container terminal automation might offer many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A robust lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure lane positioning robustness. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions and tested the robustness of the lane detection method with stochastic noise.

• Journal of Digital Contents Society
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• v.5 no.1
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• pp.87-94
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• 2004

In this paper, the digital watermarking algorithm is proposed using CDMA technique for protection of the mobile contents in the mobile environment. The digital watermarking was designed to robust the errors in the mobile environment where pathloss, multipath fading, interference, and noise exist. In case of the multimedia content service in the mobile environment, the construction method of the watermark, the algorithm of insertion and detection are also proposed. The watermark consists of the information of the mobile user. Invisibility and robustness required in watermarking are etimated. It is observed that PSNR of the mobile content inserted the watermark is 90.31 dB, and the signal processing and noise attack are also robust. Especially, because random noise occurs in wireless transmission can overcome, the proposed watermarking algorithm is adequate for protection of the multimedia contents in the mobile environment.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.469-474
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• 2018

As urban population increases, research on urban environmental noise is getting more attention. In this study, we classify the abnormal noise occurring in traffic situation by using a deep learning algorithm which shows high performance in recent environmental noise classification studies. Specifically, we classify the four classes of tire skidding sounds, car crash sounds, car horn sounds, and normal sounds using convolutional neural networks. In addition, we add three environmental noises, including rain, wind and crowd noises, to our training data so that the classification model is more robust in real traffic situation with environmental noises. Experimental results show that the proposed traffic sound classification model achieves better performance than the existing algorithms, particularly under harsh conditions with environmental noises.

• ETRI Journal
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• v.26 no.3
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• pp.273-276
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• 2004

We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.73-76
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• 2001

In this paper, we utilize a HVS(Human Visual System) watermarking method where watermarks are embedded in a DFT domain. The HVS watermarking method is robust for attacks like JPEC, filtering, noise, etc. But, when images are attacked by basic geometric attacks as cropping, scaling, rotation, a watermarks may not be detected. In this paper, we introduce the HVS watermarking method that inserts references In a domain of LSB(Least Significant Bit) of image. Experimental results show that the proposed method based on HVS watermarking method gives more robustness to the basic geometric attacks compared with original HVS watermarking methods.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.65-68
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• 2000

This paper describes an approach for extracting invariant features using a view-based representation and recognizing an object with a high speed search method in FLIR. In this paper, we use a reformulated eigenspace technique based on robust estimation for extracting features which are robust for outlier such as noise and clutter. After extracting feature, we recognize an object using a partial distance search method for calculating Euclidean distance. The experimental results show that the proposed method achieves the improvement of recognition rate compared with standard PCA.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.239-240
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• 2007

In this paper, a robust adaptive backstepping controller will be proposed for the speed control of permanent magnet synchronous motors in using electrical vehicles. Stator resistance, damping coefficient, load torque are considered as uncertainties and noise generated at applying load torque to motor is also considered. It shows that the backstepping algorithm can be used to solve the problems of nonlinear system very well and robust controller can be designed without the variation of adaptive law. Simulation results are provided to demonstrate the effectiveness of the Proposed controller.