• 로봇학회논문지
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• 제4권4호
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• pp.312-319
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• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.262-269
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involved reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constructs. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model computational experiments using a commercial genetic algorithm based optimizer. The results show that the real size problems we encountered can be solved In reasonable time

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.258-260
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• 2007

Nowadays the automotive circuit design becomes more complicated a practical modern car circuit usually contains thousands of wires. So the error connection between connector and pins becomes more difficult to be located. This paper proposes a general way to locate all error wires in an automotive circuit design. Firstly, we give an exact definition of error wire to guide our job. This definition also composes the core part of our algorithm. Then we limit the area of the error wires by several steps. During these steps, we apply breadth-first search method to step over all wires under consideration of reducing time cost. In addition, we apply bidirectional stack technique to organize the data structure for algorithm optimization. This algorithm can get a result with all error wires and doubtful wires in a very efficient way. The analysis of this algorithm shows that the complexity is linear. We also discuss some possible improvement of this algorithm.

• 정보통신설비학회논문지
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• 제10권2호
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• pp.53-61
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• 2011

This research presents an adaptive fast motion estimation (ME) computation on the stage of uneven multi-hexagon grid search (UMHGS) algorithm included in an unsymmetrical-cross multi-hexagon-grid search (UMHexagonS) in H.264 standard. The proposed adaptive method is based on statistical analysis and previously obtained motion vectors to reduce the computational complexity of ME. For this purpose, the algorithm is decomposed into three processes: skipping, terminating, and reducing search areas. Skipping and terminating are determined by the statistical analysis of the collected minimum SAD (sum of absolute difference) and the search area is constrained by the slope of previously obtained motion vectors. Simulation results show that 13%-23% of ME time can be reduced compared with UMHexagonS, while still maintaining a reasonable PSNR (peak signal-to-noise ratio) and average bitrates.

• 한국산업정보학회논문지
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• 제7권2호
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• pp.68-73
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• 2002

빠른 수렴속도를 얻기 위해서 LS(Least Square)에 기초한 적응 알고리즘에 대한 연구가 많이 이루어지고 있다. 본 논문에서는 수렴속도의 향상 그리고 계산량의 감소를 위하여 웨이브렛 기반 적응알고리즘을 제안하고, 음성신호의 특성에 따라서 두 가지 구조의 형태로 적응잡음 제거기에 적용시켰다. 컴퓨터 시뮬레이션을 통하여 기존의 시간영역 적응알고리즘, 주파수영역 적응알고리즘 그리고 제안한 알고리즘을 적응잡음제거기에 적용하여 비교하였다. 그 결과 제안한 알고리즘은 음성을 사용하는 적응신호처리 분야에 적합하다는 것을 확인하였다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2014년도 제49차 동계학술대회논문집 22권1호
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• pp.1-4
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• 2014

Although physical modeling synthesis is becoming more and more efficient in rich and natural high-quality sound synthesis, its high computational complexity limits its use in portable devices. This constraint motivated research of single-instruction multiple-data many-core architectures that support the tremendous amount of computations by exploiting massive parallelism inherent in physical modeling synthesis. Since no general consensus has been reached which grain sizes of many-core processors and memories provide the most efficient operation for sound synthesis, design space exploration is conducted for seven processing element (PE) configurations. To find an optimal PE configuration, each PE configuration is evaluated in terms of execution time, area and energy efficiencies. Experimental results show that all PE configurations are satisfied with the system requirements to be implemented in portable devices.

• 한국시뮬레이션학회논문지
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• 제12권1호
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• pp.59-71
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• 2003

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Management (SCM). One of the key issues in the current SCM research area involves reducing both production and distribution costs. The purpose of this study is to determine the optimum quantity of production and transportation with minimum cost in the supply chain network. We have presented a mathematical model that deals with real world factors and constraints. Considering the complexity of solving such model, we have applied the genetic algorithm approach for solving this model using a commercial genetic algorithm based optimizer. The results for computational experiments show that the real size problems we encountered can be solved in reasonable time.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.928-931
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• 2003

This paper presents a digit-serial/parallel multiplier for finite fields GF(2m). The hardware requirements of the implemented multiplier are less than those of the existing multiplier of the same class, while processing time and area complexity. The implemented multiplier possesses the features of regularity and modularity. Thus, it is well suited to VLSI implementation. If the implemented digit-serial multiplier chooses the digit size D appropriately, it can meet the throughput requirement of a certain application with minimum hardware. The multipliers and squarers analyzed in this paper can be used efficiently for crypto processor in Elliptic Curve Cryptosystem.

• ETRI Journal
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• 제44권3호
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• pp.379-388
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• 2022

This study proposes a novel low-complexity algorithm for computing inverse fast Fourier transform (IFFT)/fast Fourier transform (FFT) operations in binary phase shift keying-modulated orthogonal frequency division multiplexing (OFDM) communication systems without requiring any twiddle factor multiplications. The peak-to-average power ratio (PAPR) reduction capacity of an efficient PAPR reduction technique, that is, H-SLM method, is evaluated using the proposed IFFT algorithm without any complex multiplications, and the impact of oversampling factor for the accurate calculation of PAPR is analyzed. The power spectral density of an OFDM signal generated using the proposed multiplierless IFFT algorithm is also examined. Moreover, the bit-error-rate performance of the H-SLM technique with the proposed IFFT/FFT algorithm is compared with the classical methods. Simulation results show that the proposed IFFT/FFT algorithm used in the H-SLM method requires no complex multiplications, thereby minimizing power consumption as well as the area of IFFT/FFT processors used in OFDM communication systems.

• 반도체디스플레이기술학회지
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• 제22권2호
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• pp.128-132
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• 2023

Recently, with the development of deep learning technology, research on pedestrian attribute recognition technology using deep neural networks has been actively conducted. Existing pedestrian attribute recognition techniques can be obtained in such a way as global-based, regional-area-based, visual attention-based, sequential prediction-based, and newly designed loss function-based, depending on how pedestrian attributes are detected. It is known that the performance of these pedestrian attribute recognition technologies varies greatly depending on the type of backbone network that constitutes the deep neural networks model. Therefore, in this paper, several backbone networks are applied to the baseline pedestrian attribute recognition model and the performance changes of the model are analyzed. In this paper, the analysis is conducted using Resnet34, Resnet50, Resnet101, Swin-tiny, and Swinv2-tiny, which are representative backbone networks used in the fields of image classification, object detection, etc. Furthermore, this paper analyzes the change in time complexity when inferencing each backbone network using a CPU and a GPU.