• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.159-164
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• 2022

The linear assignment problem (LAP) and linear bottleneck assignment problem (LBAP) has been unknown the algorithm to solve the optimal solution within polynomial-time. These problems are classified by NP-hard. Therefore, we can be apply metaheuristic methods or linear programming (LP) software package or Hungarian algorithm (HA) with O(m⁴) computational complexity. This paper suggests polynomial time algorithm with O(mn)=O(m²),m=n time complexity to LAP and LBAP. The select-delete method is simply applied to LAP, and the delete-select method is used to LBAP. For the experimental data without the unique algorithm can be apply to whole data, the proposed algorithm can be obtain the optimal solutions for whole data.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of Advanced Navigation Technology
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• v.22 no.4
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• pp.325-335
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• 2018

Limited access to state information in the design of a feedback controller has brought out a significant amount of research on the design of an output feedback controller. Despite its long endeavor to find an optimal one, it is still an open problem. Thus, we focus on the comparison of existing states of arts in the design of a static output feedback controller in terms of stability and complexity so as to find further research direction in this field. To this end, we present eight design methods in a unified presentation. We also provide the complete description of algorithms which can be applicable to any system configuration. Stability performance and complexity in terms of processing time are evaluated through numerical simulations. Simulation results show that the algebraic controller (AC) algorithm [20] has the smallest complexity while the scaling linear matrix inequality (SLMI) algorithm [18] seems to achieve the best stability in most cases with much higher complexity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.690-695
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• 2014

This paper presents a modified CCI image interpolation method based on the even-odd decomposition (EOD). The CCI method is a well-known technique to interpolate images. Although the method provides better image quality than the linear interpolation, its complexity still is a problem. To remedy the problem, this paper introduces analysis on the EOD decomposition of CCI and then proposes a reduced CCI interpolation in terms of complexity, providing better image quality in terms of PSNR. To evaluate the proposed method, we conduct experiments and complexity comparison. The results indicate that our method do not only outperforms the existing methods by up to 43% in terms of MSE but also requires low-complexity with 37% less computing time than the CCI method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.10a
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• pp.36-48
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• 1994

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1786-1792
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• 2015

Random linear network coding (RLNC) is widely employed to enhance the reliability of wireless multicast. In RLNC encoding/decoding, Galois Filed (GF) arithmetic is typically used since all the operations can be performed with symbols of finite bits. Considering the architecture of commercial computers, the complexity of arithmetic operations is constant regardless of the dimension of GF m, if m is smaller than 32 and pre-calculated tables are used for multiplication/division. Based on this, we show that the complexity of RLNC inversely proportional to m. Considering additional overheads, i.e., the increase of header length and memory usage, we determine the practical value of m. We implement RLNC in a commercial computer and evaluate the codec throughput with respect to the type of the tables for multiplication/division and the number of original packets to encode with each other.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.3
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• pp.112-118
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• 2014

As higher quality of image is required for digital image scaling, longer processing time is required. Therefore the technology that can make higher quality image quickly is needed. We propose the double linear-cubic convolution interpolation which creates the high quality image with low complexity and hardware resources. The proposed interpolation methods which are made up of four one-dimensional linear interpolations and one one-dimensional cubic convolution perform linear-cubic convolution interpolation in horizontal and vertical direction. When compared in aspects of peak signal-to-noise ratio(PSNR), performance time and amount of hardware resources, the proposed interpolation provided better PSNR, low complexity and less hardware resources than bicubic convolution interpolation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1243-1263
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• 2018

The two-stage linear discrimination analysis (TSLDA) is a feature extraction technique to solve the small size sample problem in the field of image recognition. The TSLDA has retained all subspace information of the between-class scatter and within-class scatter. However, the feature information in the four subspaces may not be entirely beneficial for classification, and the regularization procedure for eliminating singular metrics in TSLDA has higher time complexity. In order to address these drawbacks, this paper proposes an improved two-stage linear discriminant analysis (Improved TSLDA). The Improved TSLDA proposes a selection and compression method to extract superior feature information from the four subspaces to constitute optimal projection space, where it defines a single Fisher criterion to measure the importance of single feature vector. Meanwhile, Improved TSLDA also applies an approximation matrix method to eliminate the singular matrices and reduce its time complexity. This paper presents comparative experiments on five face databases and one handwritten digit database to validate the effectiveness of the Improved TSLDA.

• ETRI Journal
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• v.37 no.1
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• pp.165-174
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• 2015

In this paper, we focus on a novel technique called the cube-linear attack, which is formed by combining cube attacks with linear attacks. It is designed to recover the secret information in a probabilistic polynomial and can reduce the data complexity required for a successful attack in specific circumstances. In addition to the different combination strategies of the two attacks, two cube-linear schemes are discussed. Applying our method of a cube-linear attack to a reduced-round Trivium, as an example, we get better linear cryptanalysis results. More importantly, we believe that the improved linear cryptanalysis technique introduced in this paper can be extended to other ciphers.

• Journal of the Korean Institute of Telematics and Electronics D
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• v.34D no.11
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• pp.1-8
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• 1997

In this paper, we propose a new method for the improvement of linearizing and adaptive convergence charateristics of the feedforward linear power amplifier. In this circuit, errors at the signal cancellation stage can be compensated at the error cancellation stage and the overall linearizaton and adaptation characteristics of the linear amplifier are improved. The broadband characteristics and linearizing capability are improved without increasing the complexity of circuits and the signal processing structure.