• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.105-106
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• 2012

In this paper, discrete wavelet transform using a PV system covers how the detection of a islanding. Connection point occur exclusively in Grid when the grid voltage and current operation of the wavelet coefficients by changing features will determine if islanding operation. The proposed method has simple computation and fast decision time has the advantage. DSP-based controller through the experiment proved the validity of the proposed method.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.1-9
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• 2009

In this paper, proposed digital image watermarking technique with lifting wavelet transformation. This watermark technique can be easily extended in video content fields. Therefore, we apply this watermark technique to layered depth image structure that is efficient compression method of multi-view video with depth images. This application steps are very simple, because watermark is inserted only reference image. And watermarks of the other view images borrow from reference image. Each view image of multi-view video may be guaranteed authentication and copyright.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.96-102
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• 2005

Acoustic Emission(AE) technique has been applied to not only material characterization evaluation but also on-line monitoring of the structural integrity. The AE source location technique is very important to identify the source, such as crack, leak detection. Since the AE waveforms obtained from sensors are very difficult to distinguish the defect signals, therefore, it is necessary to consider the signal analysis of the transient wave-form. In this study, we have divided the region of interest into a set finite elements, and calculated the arrival time differences between sensors by using the velocities at every degree from 0 to 90. A new technique for the source location of acoustic emission in fiberboard plates has been studied by introducing Wavelet Transform(WT) do-noising technique. WT is a powerful tool for processing transient signals with temporally varying spectra. If the WT de-noising was employed, we could successfully filter out the errors of source location in fiberboard plates by arrival time difference method. The accuracy of source location appeared to be significantly improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.291-298
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• 2019

In this paper, we propose a Fresnel transform method using various wavelet functions to efficiently decompose digital holograms. After implementing the proposed wavelet function-based Fresnelet transforms, we apply it to the digital hologram and analyze the energy characteristics of the coefficients. The implemented wavelet transform-based Fresnelet transform is well suited for reconstructing and processing holograms which are optically obtained or generated by computer-generated hologram technique. After analyzing the characteristics of the spline function, we discuss wavelet multiresolution analysis method based on it. Through this process, we proposed a transform tool that can effectively decompose fringe patterns generated by optical interference phenomena. We implement Fresnelet transform based on wavelet function with various decomposition properties and show the results of decomposing fringe pattern using it. The results show that the energy distribution of the coefficients is significantly different depending on whether the random phase is included or not.

• Journal of Korea Water Resources Association
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• v.45 no.12
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• pp.1321-1330
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• 2012

In this study, the daily inflow at the basin of Chungju dam is predicted using wavelet-artificial neural network for nonlinear model. Time series generally consists of a linear combination of trend, periodicity and stochastic component. However, when framing time series model through these data, trend and periodicity component have to be removed. Wavelet transform which is denoising technique is applied to remove nonlinear dynamic noise such as trend and periodicity included in hydrometeorological data and simple noise that arises in the measurement process. The wavelet-artificial neural network (WANN) using data applied wavelet transform as input variable and the artificial neural network (ANN) using only raw data are compared. As a results, coefficient of determination and the slope through linear regression show that WANN is higher than ANN by 0.031 and 0.0115 respectively. And RMSE and RRMSE of WANN are smaller than those of ANN by 37.388 and 0.099 respectively. Therefore, WANN model applied in this study shows more accurate results than ANN and application of denoising technique through wavelet transforms is expected that more accurate predictions than the use of raw data with noise.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.841-844
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• 2001

This paper introduces a new technique for estimating the speed of a mobile station in a wireless system. The proposed method is based on the feature extraction of the received signal envelope. The undecimated discrete wavelet transform via lifting captures local minimum points of the received signal, which is used for the speed estimation. This technique requires neither knowledge of the average received power of the nonstationary signal nor adaptation of a temporal observation window, in contrast to other speed estimators given in the literature. Simulations show that the proposed speed estimator tracks the variable speed of the mobile station.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.6
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• pp.78-84
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• 2000

In this paper, the diagnosis technique was proposed by measuring and analyzing ultrasonic signals caused by partial discharge on the interface of cable joint. The measured ultrasonic signal was filtered by wavelet transform, and then the dominant signal of filtered signal was analyzed by fast fourier transform(FFT). As a result, it was confirmed that different characteristics were obtained with the moisture and the metal powder on the interface of cable joint and with voltage increment.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.705-708
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• 2005

Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2711-2713
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• 2005

This paper presents the tracking control method of robotic systems with uncertainties using self recurrent wavelet neural network (SRWNN) via the backstepping design technique. The SRWNN is used as the uncertainty observer of the robotic systems. The adaptation laws for weights of the robotic systems are induced from the Lyapunov stability theorem, which are used for on-line controlling robotic systems. Computer simulations of a three-link robot manipulator with uncertainties verify the validity of the proposed SRWNN controller.