• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.709-719
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• 1997

Performance of an algorithm can be mesaurde from serval aspects.Suppose thre is a query formulation al-gorithm.Even though this algorithm shows high retrival performance, ie, high recall and percision, retriveing items can rake a long time.In this study, we time complexity of automatic query reformulation algorithms, named the query Tree, DNF method, and Dillon's method, and comparethem in theoretical and practical aspects using a tral-time performance)the absolute times for each algorithm to fromulate a query)in a Sun SparcStation 2. In experiments using three test sets, CSCM, CISI, and Medlars, the query Tree algorithm was the fastest among the three algorithms tested.

• ETRI Journal
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• v.37 no.3
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• pp.491-501
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• 2015

Spectrum sensing is an elementary function in cognitive radio designed to monitor the existence of a primary user (PU). To achieve a high rate of detection, most techniques rely on knowledge of prior spectrum patterns, with a trade-off between high computational complexity and long sensing time. On the other hand, blind techniques ignore pattern matching processes to reduce processing time, but their accuracy degrades greatly at low signal-to-noise ratios. To achieve both a high rate of detection and short sensing time, we propose fast spectrum sensing with coordinate system (FSC) - a novel technique that decomposes a spectrum with high complexity into a new coordinate system of salient features and that uses these features in its PU detection process. Not only is the space of a buffer that is used to store information about a PU reduced, but also the sensing process is fast. The performance of FSC is evaluated according to its accuracy and sensing time against six other well-known conventional techniques through a wireless microphone signal based on the IEEE 802.22 standard. FSC gives the best performance overall.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.11-18
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• 2017

Finite field arithmetic has been extensively used in error correcting codes and cryptography. Low-complexity and high-speed designs for finite field arithmetic are needed to meet the demands of wider bandwidth, better security and higher portability for personal communication device. In particular, cryptosystems in GF($2^m$) usually require computing exponentiation, division, and multiplicative inverse, which are very costly operations. These operations can be performed by computing modular AB multiplications or modular $AB^2$ multiplications. To compute these time-consuming operations, using $AB^2$ multiplications is more efficient than AB multiplications. Thus, there are needs for an efficient $AB^2$ multiplier architecture. In this paper, we propose a low latency Montgomery $AB^2$ multiplier using redundant representation over GF($2^m$). The proposed $AB^2$ multiplier has less space and time complexities compared to related multipliers. As compared to the corresponding existing structures, the proposed $AB^2$ multiplier saves at least 18% area, 50% time, and 59% area-time (AT) complexity. Accordingly, it is well suited for VLSI implementation and can be easily applied as a basic component for computing complex operations over finite field, such as exponentiation, division, and multiplicative inverse.

• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.111-117
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• 2021

The delivery problem on a graph is that of minimizing the object delivery time from one vertex to another vertex on a graph with m vertices using n various speed robot agents. In this paper, we propose two optimal solution algorithms for the delivery problem on a graph with time complexity of O(㎥n) and O(㎥). After preprocessing to obtain the shortest path for all pairs of the graph, our algorithm processed by obtaining the shortest delivery path in the order of the vertices with the least delivery time. Assuming that the graph reflects the terrain on which to solve the problem, our O(㎥) algorithm actually has a time complexity of O(㎡n) as only one preprocessing is required for the various deployment of n robot agents.

• 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.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.305-314
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• 2017

Clustering is a method that collects data objects into groups based on their similary. Performance of the state-of-the-art clustering methods is different according to the data characteristics. There have been numerous studies that performed experiments to compare the accuracy of the state-of-the-art clustering methods by applying various kinds of datasets. A common problem of these studies is that they only consider clustering algorithms that yield the most accurate results for a particular dataset. They do not consider what factors affect the execution time of each clustering method and how they are affected. Nevertheless, execution time is an important factor in clustering performance if there is no significant difference in accuracy. In order to solve the problems of the existing research, through a series of experiments using various types of datasets, we compare the accuracy of four representative clustering methods. In addition, we perform practical clustering performance comparisons by deriving time complexity and identifying factors that influences to its performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.79-89
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• 2011

Recent development of embedded processors makes it possible to play back video contents in real-time on portable devices. Because of their limited battery capacity and low computational performance, however, portable devices still have significant problems in real-time decoding of high quality or high resolution compressed video. Although previous approaches are successful in achieving complexity-scalable decoder by controlling computational complexity of decoding elements, they cause significant objective quality loss coming from mismatch between encoder and decoder. In this paper, we propose a selective B slice skip-decoding method to implement a low complexity video decoder. The proposed method performs selective skip decoding process of B slice which satisfies the proposed conditions. The skipped slices are reconstructed by simple reconstruction method utilizing adjacent reconstructed pictures. Experimental result shows that proposed method not only reduces computational complexity but also maintains subjective visual quality.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.12
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• pp.29-40
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• 2008

The efficient hardware design of finite field multiplication is an very important research topic for and efficient $f(x)=x^n+x^k+1$ implementation of cryptosystem based on arithmetic in finite field GF($2^n$). We used special generating trinomial to construct a bit-parallel multiplier over finite field with low space complexity. To reduce processing time, The hardware architecture of proposed multiplier is similar with existing Mastrovito multiplier. The complexity of proposed multiplier is depend on the degree of intermediate term $x^k$ and the space complexity of the new multiplier is $2k^2-2k+1$ lower than existing multiplier's. The time complexity of the proposed multiplier is equal to that of existing multiplier or increased to $1T_X(10%{\sim}12.5%$) but space complexity is reduced to maximum 25%.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.80.2-80
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• 2002

The problem of sound source localization is to determine the position of sound sources using the measurement of the acoustic signals received by microphones. To develop a good sound source localization system which is applicable to a mobile platform such as robots, a time delay estimator with low computational complexity and robustness to background noise or reverberations is necessary. In this paper, an explicit adaptive time delay estimation method for a sound source localization system is proposed. Proposed explicit adaptive time estimation algorithm employs direct adaptation of the delay parameter using a transform-based optimization technique, rather than...

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.37-43
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• 2020

In this paper, we propose an efficient AB² multiplication algorithm using SPB(shifted polynomial basis) over finite fields. Using the feature of the SPB, we split the equation for AB² multiplication into two parts. The two partitioned equations are executable at the same time, and we derive an algorithm that processes them in parallel. Then we propose an efficient semi-systolic AB² multiplier based on the proposed algorithm. The proposed multiplier has less area-time (AT) complexity than related multipliers. In detail, the proposed AB² multiplier saves about 94%, 87%, 86% and 83% of the AT complexity of the multipliers of Wei, Wang-Guo, Kim-Lee, Choi-Lee, respectively. Therefore, the proposed multiplier is suitable for VLSI implementation and can be easily adopted as the basic building block for various applications.