• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.234-241
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• 2007

Effective tools which can alleviate the complexity and computational load problem in collision-free motion planning for multi-agent system have steadily been demanded in robotics field. To reduce the complexity, the extended collision map (ECM) which adopts decoupled approach and prioritization is already proposed. In ECM, the collision regions which represent the potential collision of robots are calculated using the computational power; the complexity problem is not resolved completely. In this paper, we propose a mathematical analysis of the extended collision map; as a result, we formulate the collision region as an equation with 5-8 variables. For mathematical analysis, we introduce realistic assumptions as follows; the path of each robot can be approximated to a straight line or an arc and every robot moves with uniform velocity or constant acceleration near the intersection between paths. Our result reduces the computational complexity in comparison with the previous result without losing optimality, because we use simple but exact equations of the collision regions. This result can be widely applicable to coordinated multi-agent motion planning.

• ETRI Journal
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• v.36 no.4
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• pp.528-536
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• 2014

High Efficiency Video Coding (HEVC) is the most recent video coding standard to achieve a higher coding performance than the previous H.264/AVC. In order to accomplish this improved coding performance, HEVC adopted several advanced coding tools; however, these cause heavy computational complexity. Similar to previous video coding standards, motion estimation (ME) of HEVC requires the most computational complexity; this is because ME is conducted for three inter prediction modes - namely, uniprediction in list 0, uniprediction in list 1, and biprediction. In this paper, we propose an efficient inter prediction mode (EIPM) decision method to reduce the complexity of ME. The proposed EIPM method computes the priority of all inter prediction modes and performs ME only on a selected inter prediction mode. Experimental results show that the proposed method reduces computational complexity arising from ME by up to 51.76% and achieves near similar coding performance compared to HEVC test model version 10.1.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1330-1350
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• 2022

As a preprocessing operation of transmitter antennas, the hybrid precoding is restricted by the limited computing resources of the transmitter. Therefore, this paper proposes a novel hybrid precoding that guarantees the communication efficiency with low complexity and a fast computational speed. First, the analog and digital precoding matrix is derived from the maximum eigenvectors of the channel matrix in the sub-connected architecture to maximize the communication rate. Second, the extended power iteration (EPI) is utilized to obtain the maximum eigenvalues and their eigenvectors of the channel matrix, which reduces the computational complexity caused by the singular value decomposition (SVD). Third, the Aitken acceleration method is utilized to further improve the convergence rate of the EPI algorithm. Finally, the hybrid precoding based on the EPI method and the Aitken acceleration algorithm is evaluated in millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. The experimental results show that the proposed method can reduce the computational complexity with the high performance in mmWave massive MIMO systems. The method has the wide application prospect in future wireless communication systems.

• Journal of applied mathematics & informatics
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• v.8 no.3
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• pp.959-973
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• 2001

We shall discuss one of some techniques needed to analyze algorithms. It is called a big-O function technique. The measures of efficiency of an algorithm have two cases. One is the time used by a computer to solve the problem using this algorithm when the input values are of a specified size. The other one is the amount of computer memory required to implement the algorithm when the input values are of a specified size. Mainly, we will restrict our attention to time complexity. To figure out the Time Complexity in nonlinear problems of Numerical Analysis seems to be almost impossible.

• Journal of Computing Science and Engineering
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• v.10 no.2
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• pp.68-73
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• 2016

An efficient texture compression method is proposed based on a block matching process between the current block and the previously encoded blocks. Texture mapping is widely used to improve the quality of rendering results in real-time applications. For fast texture mapping, it is important to find an optimal trade-off between compression efficiency and computational complexity. Low-complexity methods (e.g., ETC1 and DXT1) have often been adopted in real-time rendering applications because conventional compression methods (e.g., JPEG) achieve a high compression ratio at the cost of high complexity. We propose a block matching-based compression method that can achieve a higher compression ratio than ETC1 and DXT1 while maintaining computational complexity lower than that of JPEG. Through a comparison between the proposed method and existing compression methods, we confirm our expectations on the performance of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.354-357
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• 2013

The filtering algorithm is used very frequently in the preprocessing stage of many image processing algorithms in computer vision processing. Because video signals are two-dimensional signals, computaional complexity is very high. To reduce the complexity, separable filters and the factorization theorem is applied to the filtering operation. As a result, it is shown that a significant reduction in computational complexity is achieved, although the experimental results could be slightly different depending on the condition of the image.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.620-626
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• 2014

In this paper, we propose a parallel collaborative sphere decoder with a scalable architecture promising quasi-maximum likelyhood performance with a relatively small amount of computational resources. This design offers a hardware-friendly algorithm using a modified node operation through fixing the variable complexity of the critical path caused by the sequential nature of the conventional sphere decoder (SD). It also reduces the computational complexity compared to the fixed-complexity sphere decoder (FSD) algorithm by tree pruning using collaboratively operated node operators. A Monte Carlo simulation shows that our proposed design can be implemented using only half the parallel operators compared to the approach using an ideal fully parallel scheme such as FSD, with only about a 7% increase of the normalized decoding time for MIMO dimensions of $16{\times}16$ with 16-QAM modulation.

• ETRI Journal
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• v.28 no.2
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• pp.145-154
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• 2006

In the decoding process associated with interframe wavelet coding, the inverse wavelet transform requires high computational complexity. However, as video technology starts to pervade all aspects of our lives, decoders are becoming required in various devices such as PDAs, notebooks, PCs, and set-top boxes. Therefore, a decoder's complexity needs to be adapted to the processor's computational power, and consequently a low-complexity codec is also required for scalable video coding. In this paper, we propose a method of controlling and lowering the complexity of the spatial wavelet transform while sustaining the same coding efficiency as that currently afforded. In addition, the proposed method may alleviate the ringing effect for slowly changing image sequences.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.201-208
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• 2012

In this paper, the hardware design of rate control for real-time video encoded is proposed. In the proposed method, a quadratic rate distortion model with high-computational complexity is not used when quantization parameter values are being decided. Instead, for low-computational complexity, average complexity weight values of frames are used to calculate QP. For high speed and low computational prediction, the MAD is predicted based on the coded basic unit, using spacial and temporal correlation in sequences. The rate control is designed with the hardware for fast QP decision. In the proposed method, a quadratic rate distortion model with high-computational complexity is not used when quantization parameter values are being decided. Instead, for low-computational complexity, average complexity weight values of frames are used to calculate QP. In addition, the rate control is designed with the hardware for fast QP decision. The execution cycle and gate count of the proposed architecture were reduced about 65% and 85% respectively compared with those of previous architecture. The proposed RC was implemented using Verilog HDL and synthesized with UMC $0.18{\mu}m$ standard cell library. The synthesis result shows that the gate count of the architecture is about 19.1k with 108MHz clock frequency.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.1-8
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• 2018

This paper proposes a low complexity super resolution algorithm for frequency modulated continuous wave (FMCW) radar systems for foreign object debris (FOD) detection. FOD radar has a requirement to detect foreign object in small units in a large area. However, The fast Fourier transform (FFT) method, which is most widely used in FMCW radar, has a disadvantage in that it can not distinguish between adjacent targets. Super resolution algorithms have a significantly higher resolution compared with the detection algorithm based on FFT. However, in the case of the large number of samples, the computational complexity of the super resolution algorithms is drastically high and thus super resolution algorithms are difficult to apply to real time systems. In order to overcome this disadvantage of super resolution algorithm, first, the proposed algorithm coarsely obtains the frequency of the beat signal by employing FFT. Instead of using all the samples of the beat signal, the number of samples is adjusted according to the frequency of the beat signal. By doing so, the proposed algorithm significantly reduces the computational complexity of multiple signal classifier (MUSIC) algorithm. Simulation results show that the proposed method achieves accurate location even though it has considerably lower complexity than the conventional super resolution algorithms.