• 한국멀티미디어학회논문지
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• 제19권2호
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• pp.200-208
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• 2016

Compressed sensing is a signal processing technique for efficiently acquiring and reconstructing in an under-sampled (i.e., under Nyquist rate) representation. A block compressed sensing with projected Landweber (BCS-SPL) framework is most widely known, but, it has high computational complexity at decoder side. In this paper, by introducing adaptive exit criteria instead of fixed exit criteria to SPL framework, an effective fast algorithm is designed in such a way that it can utilize efficiently the sparsity property in DCT coefficients during the iterative thresholding process. Experimental results show that the proposed algorithm results in the significant reduction of the decoding time, while providing better visual qualities than conventional algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 학술대회 논문집 전문대학교육위원
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• pp.141-145
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• 2007

Using the New Fast Walsh Transform algorithm, we present a new algorithm which reduces the computational amount, and it can consequently calculate the real and imaginary components for current and voltage signals of power system in sampling intervals. The calculation amount is reduced to 2X(m-1) at m samples to measure full harmonics using developed algorithm. When in single harmonic measuring, it needs only 2(log2N-1)+1 additions and subtractions. We developed hardware device for testing, and tested the developed algorithm by measuring real and imaginary components.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2013년도 하계학술대회
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• pp.173-175
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• 2013

In this paper, we propose a fast and low-complexity Motion Estimation (ME) algorithm for High Efficiency Video Coding (HEVC). Motion estimation occupies 77~81% of the amount of computation in HEVC. After all, the main key of codec implementation is to find a fast and low-complexity motion estimation algorithm and architecture. The proposed algorithm uses only 1% of the amount of operations compared to full search algorithm while maintaining compression performance with slight loss of 0.6% (BDBR).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.529-531
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• 2005

A block-based fast motion estimation algorithm is proposed in this paper to perform motion estimation based on the efficiently reduced search ranges in MPEG-4(ERS). This algorithm divides the search areas into several small search areas and the candidate small search area that has the lowest average of sum norm difference between current macroblock and candidate macroblock is chosen to perform block motion estimation using the Nobel Successive Elimination Algorithm (NSEA). Experimental results of the proposed algorithm show that the averaging PSNR improvement is better maximum 0.125 dB than other tested algorithms and bit saving effect is maximum 20kbps for some tested sequences in low-bit rate circumstance.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
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• pp.295-298
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• 2002

This paper presents a fast block-matching algorithm to improve the conventional Three-Step Search (TSS) based method. The proposed Comparison Fast Block Matching Algorithm (CFBMA) begins with DAB for adaptive search range to choose searching method, and searches a part of search window that has high possibility of motion vector like other partial search algorithms. The CFBMA also considers the opposite direction to reduce local minimum, which is ignored in almost conventional based partial search algorithms. CFBMA uses the summation half-stop technique to reduce the computational load. Experimental results show that the proposed algorithm achieves the high computational complexity compression effect and very close or better image quality compared with TSS, SES, NTSS based partial search algorithms.

• 한국초전도ㆍ저온공학회논문지
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• 제21권4호
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• pp.53-58
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• 2019

The critical current is one of the key parameters of high temperature superconducting (HTS) racetrack coils. Therefore, it is significant to calculate critical currents of HTS coils. This paper introduces a fast iterative algorithm for calculating the critical current of second generation (2G) HTS coils. This model does not need to solve long charging transients which greatly reduced the amount of calculation. To validate this model, the V-I curve of four 2G HTS double racetrack coils are measured. The effect of the silicon steel sheet on the critical current of the racetrack coil is also studied based on this algorithm.

• 한국통신학회논문지
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• 제22권12호
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• pp.2706-2713
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• 1997

The fast implementation algorithm of M-band discrete wavelet transform is propsed using the factorization of lossless matrix when the length of discrete orthogonal wavelet bases equals to 2M. In computational complexity when direct filtering method is employed, the number of multiplicationand addition is (2M$^{2}$) and (2M$^{2}$ -M), respectively. But by proposed algorithm, it can be reduced to (M$^{2}$+M) and (M$^{2}$+2M-1), respectively. and it is possible to reduce the compuatational complexity further when unitary matrix employed to design the discrete or thogonal wavelet basis has the fast algorithm.

• ETRI Journal
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• 제45권6호
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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.

• 전자공학회논문지B
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• 제29B권4호
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• pp.58-65
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• 1992

In this paper new back propagation algorithm which adds neurons to hidden layer is proposed. this proposed algorithm is applied to the pattern recognition of written number coupled with back propagation algorithm through omitting redundant learning. Learning rate and recognition rate of the proposed algorithm are compared with those of the conventional back propagation algorithm and the back propagation through omitting redundant learning. The learning rate of proposed algorithm is 4 times as fast as the conventional back propagation algorithm and 2 times as fast as the back propagation through omitting redundant learning. The recognition rate is 96.2% in case of the conventional back propagation algorithm, 96.5% in case of the back propagation through omitting redundant learning and 97.4% in the proposed algorithm.

• 한국통신학회논문지
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• 제40권9호
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• pp.1686-1692
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• 2015

본 논문에서는 메쉬 네트워크의 이동노드에 대해 기존의 유전알고리즘을 이용한 빔형성과 같은 성능을 가지면서 빠른 수렴속도를 가지고 지역해에 빠지지 않는 개선된 유전알고리즘을 제안한다. 제안한 빔형성 유전알고리즘은 빠른 수렴속도를 얻기 위해서 교배과정에서 적합도가 높은 염색체의 일정비율을 추출하고 지역해에 빠지는 것을 방지하기 위해 하위 염색체로 교배에 사용하였다. 그리고 적합도 측정용 빔형성의 기준 빔패턴을 가우시안 함수를 이용하여 수렴속도를 더욱 빠르게 하였다. 전산모의 실험을 통하여 제안한 빔형성 유전알고리즘이 기존의 빔형성 유전알고리즘 방식과 비교하여 약 20%의 빠른 수렴속도가 향상되었음을 보였다.