• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.95-98
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• 2013

The LMS(Least Mean Square) algorithm, one of the most famous, is generally used because of tenacity and high mating spots and simplicity of realization, But it has trade-off between nonuniform collection and EMSE(Excess mean square error). To overcome this weakness, a variable step size is used widely, but it needs a lot of calculation loads. In this paper, we suggest changed algorithm in case of environment changes of cars and reduce amount of calculation as it uses original signal and noise signal of IGC(Instantaneous Gain Control) algorithm. In this paper, logarithmic function is removed because of real-time processing IGC. The performance of proposed algorithm is tested to adaptive noise canceller in automobile.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.127-129
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• 2012

Due to the prevalence of digital camera, multi-media etc. the image is being used in everyday life. However, noise always damages the image and the image denoising technology is important part for improving the image visual quality. There are many existing methods to remove noise such as wiener filter, mean filter and VisuShrink etc. However, they perform not good enough for denoising. Hence, in this paper we proposed a hybrid filter algorithm which consists of wiener filter and modified wavelet based thresholding method using adaptive threshold and thresholding function. The proposed algorithm shows not only better low frequency and high frequency property, but also the outstanding noise suppression and edge preservation properties.

• Journal of KSNVE
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• v.10 no.6
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• pp.1059-1066
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• 2000

In this paper. a new indirect feedback active noise control (ANC) scheme barred on the fundamental frequency estimation is proposed for systems with a harmonic noise. When reference signals necessary for feedforward ANC configuration are difficult to obtain, the conventional ANC algorithms for multi-tonal noise do not measure the reference signals but generate them with the estimated frequencies.$^{(4)}$ However, the beating phenomena, in which certain frequency components of the noise vanish intermittently, may make the adaptive frequency estimation difficult. The confusion in the estimated frequencies due to the beating phenomena makes the generated reference signals worthless. The proposed algorithm consists of two parts. The first part is a reference generator using the fundamental frequency estimation and the second one is the conventional feedforward control. We propose the fundamental frequency estimation algorithm using decision rules. which is insensitive to the beating phenomena. In addition, the proposed fundamental frequency estimation algorithm has good tracking capability and lower variance of frequency estimation error than that of the conventional cascade ANF method.$^{(4)}$ We are also able to control all interested modes of the noise, even which cannot be estimated by the conventional frequency estimation method because of the poor S/N ratio. We verify the performance of the proposed ANC method through simulations for the measured cabin noise of a passenger ship and the measured time-varying engine booming noise of a passenger vehicle.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.4
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• pp.318-330
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• 2013

This paper presents a high-linearity low-noise small-size programmable gain amplifier (PGA) based on a new low-noise low-distortion differential amplifier and a proposed reconfiguration technique. The proposed differential amplifier combines an inverter-based differential pair with an adaptive biasing circuit to reduce noise and distortion. The reconfiguration technique saves the chip size by half by utilizing the same differential pair for the input transconductance and load-stage, interchangeably. Fabricated in $0.18-{\mu}m$ CMOS, the proposed PGA shows a dB-linear control range of 21dB in 16 steps from -11 dB to 10 dB with a gain error of less than ${\pm}0.33$ dB, an IIP3 of 7.4~14.5 dBm, a P1dB of -7~1.2 dBm, a noise figure of 13dB, and a 3-dB bandwidth of 270MHz at the maximum gain, respectively. The PGA occupies a chip area of $0.04mm^2$ and consumes only 1.3 mA from the 1.8 V supply.

• Proceedings of the KIEE Conference
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• 2006.10b
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• pp.181-184
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• 2006

In this study, an robust adaptive backstepping controller is proposed for the speed control of separately excited DC motor with uncertainties and disturbances. Armature and field resistance, damping coefficient and 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 and experiment results are provided to demonstrate the effectiveness of the proposed controller in the future.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.173-176
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• 1996

The transient behavior of the complex-LMS adaptive filter is studied when the adaptive filter is operating on a fixed or sweeping complex frequency sine-wave signal. The first-order difference equation is derived for the mean weights and its closed form solution is obtained. The transient response is represented as a function of the eigenvectors and eigenvalues of input correlation matrix. The mean-square error of the algorithm is evaluated as well. An optimal convergence parameter and filter length can be determined for sweeping frequency sine-wave signals as a function of frequency change rate and signal and noise powers.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.16-21
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• 2005

This paper considers the problem of state estimation in linear continuous-time systems with multi-sensor environment and observation uncertainties. We propose two suboptimal filtering algorithms for these types of systems. The filtering algorithms consist of two steps: The local optimal Kalman estimates are computed at the first step. And, these local estimates are lineally fused at the second step. The implementation of the two-step filtering algorithms needs a lower memory demand than the optimal Kalman and adaptive Lainiotis-Kalman filters. In consequence of parallel structure of the proposed filters, the parallel computers can be used for their design. The examples exhibit the effect of common noise on the performance of fusion of the local Kalman estimates based on observations from different sensors and in the presence of uncertainties.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.361-362
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• 2007

We propose a contrast-controlled feature detection approach for steel radiograph image. X-ray images are low contrast, dark and high noise image. So, It is not simple to detect defects directly in automated radiography inspection system. Contrast enhancement, histogram equalization and median filter are the most frequently used techniques to enhance the X-ray images. In this paper, the adaptive control method based on contrast limited histogram equalization is compared with several histogram techniques. Through comparative analysis, CLAHE(contrast controlled adaptive histogram equalization) can enhance detection of defects better.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.631-639
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• 2014

Recently, research on Media Access Control (MAC) techniques for underwater acoustic communication has been conducted actively. For successful acoustic communication in underwater conditions, development of environmentally adaptive MAC techniques, which is taking narrow bandwidth, distance, depth, noise level, salinity, multipath and etc into account, is an especially important work. In this paper, knowledge based system is introduced not only to obtain adaptive and optimal communication parameters but also increase network efficiency and availability by requesting change of MAC techniques based on decisions from knowledge-based system Smart Decision Block (SDB). Computer simulations were also conducted to verify the performance of the proposed system in underwater conditions.