• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1097-1100
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• 1999

Due to the significant computation of full search in motion estimation, extensive research in fast motion estimation algorithms has been carried out. However, most of the algorithms have the degradation in predicted images compared with the full search algorithm. To reduce an amount of significant computation while keeping the same prediction quality of the full search, we propose a fast block-matching algorithm based on gradient magnitude of reference block without any degradation of predicted image. By using Taylor series expansion, we show that the block matching errors between reference block and candidate block are proportional to the gradient magnitude of matching block. With the derived result, we propose fast full search algorithm with adaptively determined scan direction in the block matching. Experimentally, our proposed algorithm is very efficient in terms of computational speedup and has the smallest computation among all the conventional full search algorithms. Therefore, our algorithm is useful in VLSI implementation of video encoder requiring real-time application.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.84-90
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• 2019

Tremendous computation of full search or lossless motion estimation algorithms for video coding has led development of many fast motion estimation algorithms. We still need proper control of computation and prediction quality. In the paper, we suggest an algorithm that reduces computation effectively and controls computational amount and prediction quality, while keeping prediction quality as almost the same as that of the full search. The proposed algorithm uses multiple thresholds for partial block sum and times of counting unchanged minimum position for each step. It also calculates the partial block matching error, removes impossible candidates early, implements fast motion estimation by comparing times of keeping the position of minimum error for each step, and controls prediction quality and computation easily by adjusting the thresholds. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.

• ETRI Journal
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• v.38 no.4
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• pp.695-702
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• 2016

A hierarchical approach for fast bi-dimensional empirical mode decomposition (B-EMD) is proposed. The presented approach utilizes an efficient window size determination scheme that enables the multi-level computation of the order statistics filter (OSF). Our detailed experiments show that the proposed OSF computation approach allows a significantly faster computation of an EMD without degrading the decomposition accuracy.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.7
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• pp.453-457
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• 2005

With the expansion of Internet, a variety of image databases are widely used and it is needed to select the part of an image what he wants. In contents-based image retrieval system, Zernikie moment and ART Descriptors are used fur shape descriptors in MPEC-7. This paper presents a fast computation method to determine the radius of a bounding circle that encloses an object in a binary image. With conventional methods, the whole area of the image should be scanned first and the distance from every pixel to the center point be computed. The proposed 4-directional scan method and fast circle-drawing algorithm is utilized to minimize the scanning area and reduce the number of operations fur computing the distance. Experimental results show that proposed method saves the computation time to determine the radius of a bounding circle efficiently.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.215-219
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• 2005

We consider penalized likelihood regression with exponential family responses. Parallel to recent development in Gaussian regression, the fast computation through asymptotically efficient low-dimensional approximations is explored, yielding algorithm that scales much better than the O($n^3$) algorithm for the exact solution. Also customizations of the direct cross-validation strategy for smoothing parameter selection in various distribution families are explored and evaluated.

• Journal of electromagnetic engineering and science
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• v.1 no.1
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• pp.78-82
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• 2001

For fast capacitance computation, a simple mesh refinement technique on MLFMA(Multi-Level Fast Multipole Algorithm) is proposed The triangular meshes are refined mainly in the area which has heavy charge density. The technique is applied to the capacitance extraction of three dimensional conductors. The results show good convergence with comparable accuracy. An adaptive technique concerned with MLFMA is useful to reduce computation time and the number of elements without additional computational efforts in large three dimensional problems.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.66-78
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• 2012

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retailers, respectively. It is critical to develop a standardized business process and mathematical model to respond market trends and customer requirements in the fast fashion industry. Thus, we define a product supply model that consists of forecasting, assortment plan, store capacity plan based on the visual merchandising, and production capacity plan considering quick response of the fast fashion retailers. For the forecasting, the decomposition method and multiple regression model are applied. In order to optimize inventory costs. A heuristic algorithm for the quantity supplied is designed based on the assortment plan, store capacity plan and production capacity plan. It is shown that the heuristic algorithm produces a feasible solution which outperforms the average inventory cost of a global fast fashion company.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2196-2199
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• 2003

With the development of digital signal processor(DSP), digital pulse compressor (DPC) is commonly used in radar systems. A DPC is implemented by using finite impulse response(FIR) filter algorithm in time domain or fast Fourier transform(FFT) algorithm in frequency domain. This paper compares the computation complexity tot these two methods and calculates boundary Fm filter taps that determine which of the two methods is better based on computation amount. Also, it shows that the boundary FIR filter taps for DSP, ADSP21060, and those for computation complexity have similar characteristic.

• The Journal of the Acoustical Society of Korea
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• v.31 no.7
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• pp.427-434
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• 2012

The overlap-add technique based on waveform similarity (WSOLA) method is known to be an efficient high-quality algorithm for time scaling of speech signal. The computational load of WSOLA is concentrated on the repeated normalized cross-correlation (NCC) calculation to evaluate the similarity between two signal waveforms. To reduce the computational complexity of WSOLA, this paper proposes a fast NCC computation method, in which NCC is obtained through pre-calculated sum tables to eliminate redundancy of repeated NCC calculations in the adjacent regions. While the denominator part of NCC has much redundancy irrespective of the time-scale factor, the numerator part of NCC has less redundancy and the amount of redundancy is dependent on both the time-scale factor and optimal shift value, thereby requiring more sophisticated algorithm for fast computation. The simulation results show that the proposed method reduces about 40%, 47% and 52% of the WSOLA execution time for the time-scale compression, 2 and 3 times time-scale expansions, respectively, while maintaining exactly the same speech quality of the conventional WSOLA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.160-168
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• 2011

A Frequency domain beamforming technique is widely used in sonar systems with a large number of beams and sensors. In the battlefield environment requiring real-time signal processing, it is needed to optimize the computational complexity of the spectrum computation to implement an efficient and fast frequency domain beamformer. So, in this paper, we proposed the pruned-GSFFT (pruned generalized sliding fast Fourier transform) as a new spectrum computation method. The proposed method help to reduce the computational complexity of the real-time partial spectrum computation by eliminating the redundancy between consecutive input samples and skipping the regardless frequency bands. Also the characteristics of the proposed pruned-GSFFT method and its computational complexity are compared to those of previous FFT algorithms.