• ETRI Journal
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• v.45 no.6
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• pp.1035-1045
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• 2023

We propose a novel graphics processing unit (GPU) algorithm that can handle a large-scale 3D fast Fourier transform (i.e., 3D-FFT) problem whose data size is larger than the GPU's memory. A 1D FFT-based 3D-FFT computational approach is used to solve the limited device memory issue. Moreover, to reduce the communication overhead between the CPU and GPU, we propose a 3D data-transposition method that converts the target 1D vector into a contiguous memory layout and improves data transfer efficiency. The transposed data are communicated between the host and device memories efficiently through the pinned buffer and multiple streams. We apply our method to various large-scale benchmarks and compare its performance with the state-of-the-art multicore CPU FFT library (i.e., fastest Fourier transform in the West [FFTW]) and a prior GPU-based 3D-FFT algorithm. Our method achieves a higher performance (up to 2.89 times) than FFTW; it yields more performance gaps as the data size increases. The performance of the prior GPU algorithm decreases considerably in massive-scale problems, whereas our method's performance is stable.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.1
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• pp.82-88
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• 2000

In this paper, We compare the Harr wavelet of the S+P transform with various integer coefficient filter banks and apply 9/7 ICFB to the wavelet transform. In addition, we propose a entropy-coding method that exploits the multiresolution structure and the feedback of the prediction error, and can efficiently compress the transformed image for progressive transmission. Simulation results are included to compare to the compression ratio using the S+P transform with different types of images.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.271-285
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• 2009

Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1880-1884
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• 2004

The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.144-147
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• 2005

The tire is considered as one of the Important noise sources having an influence on vehicle's performance. The Pattern noise of a tire is the transmission sound of airborne noise. On smooth asphalt road, Pattern noise is amplified with the velocity. In recent, the study on the reduction of Pattern noise is energetically processed. Pattern noise is strongly related with pitch sequence. To reduce the pattern noise, tire's designer has to randomize the sequence of pitch. The FFT is a traditional method to evaluate the level of the randomization of the pitch sequence, but gives no information on time-varying, instantaneous frequency. In the study, we found that Time-Frequency transform is a useful method to non-stationary signal such as tire noise.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.595-598
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• 1988

In this paper, a new folding algorithm for design of high density PLA's is proposed. This algorithm generates transform matrix so that programmed region of each row becomes narrow. Based on transform matrix, folding pair is selected. In the process of generating transform matrix, interval degree and dense degree are used to improve folding ratio. This paper also proposes an efficient folding pair graph which has short time of selection folding pair. This proposed algorithm is named PLAFOLII and implemented in C language on VAX-11/750 (UNIX) computer. Through various example, efficiency of this algorithm is verified.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.975-978
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• 1997

This Paper presents a high impedance fault (HIF) detection algorithm of distribution systems using wavelet transform. Two HIFs on dry soil and sandy soil were simulated on various load conditions in 22.9 kV distribution systems using EMTP, and the current wavelets were decomposed by wavelet transform. The current root mean square(rms) change, the index change rate and the relative amplitude change were used as the multi-criteria for a HIF detection. The index change rate and the relative amplitude were made using the wavelet coefficients.

• Journal of Power System Engineering
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• v.7 no.2
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• pp.29-35
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• 2003

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a classification method of diagnosing the small reciprocating compressor for refrigerators using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them ate compared with each other. This paper is focused on the development of an advanced signal classifier to automatize the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• Aerospace Engineering and Technology
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• v.8 no.2
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• pp.26-32
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• 2009

In the satellite image fusion, the most important point is to preserve both the spatial detail of panchromatic(PAN) image and the spectral information of multispectral(MS) image. Among various image fusion techniques, fusion technique using Intensity-Hue-Saturation(IHS) transform is widely used and it has advantage that computation is very simple. In this study, a fusion technique using fast IHS transform and trade-off parameter $\alpha^i$ proposed. Proposed fusion technique permits customization of the trade-off between the spectral information and spatial detail quality of the fused image through the evaluation of two quality indices: a spectral index(the spectral ERGAS) and a spatial one(the spatial ERGAS). Based on the result of experiment using IKONOS image, we confirmed the proposed fusion technique was more effective in preserving spatial detail and spectral information than existing fusion techniques using fast IHS transform.

• Journal of the Korean earth science society
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• v.28 no.7
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• pp.903-913
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• 2007

In this study, the researchers compared the S-wave velocity structures obtained by two kinds of dispersion curves: phase and group dispersions from a tidal flat located in the SW coast of the Korean peninsula. The ${\tau}-p$ stacking method was used for the phase velocity and two different methods (multiple filtering technique: MFT and continuous wavelet transform: CWT) for the phase velocity. It was difficult to separate higher modes from the fundamental mode phase velocities using the ${\tau}-p$ method, whereas the separation of different modes of group velocity were easily achieved by both MFT and CWT. Of the two methods, CWT was found to be more efficient than MFT. The spatial resolutions for the inversion results of the fundamental mode for both phase and group velocities were good for only a very shallow depth of ${\sim}1.5m$. On the other hand, the spatial resolutions were good up to ${\sim}4m$ when both the fundamental and the 1st higher mode poop velocities obtained by CWT were used for S-wave inversion. This implies that the 1st higher mode Rayleigh waves contain more information on the S-wave velocity in deeper subsurface. The researchers applied the CWT method to obtain the fundamental and the 1st higher mode poop velocities of the S-wave velocity structure of a tidal flat located in SW coast of the Korean peninsula. Thea the S-wave velocity structures were compared with the borehole description of the study area.