• Title/Summary/Keyword: Fast Computation

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Optimization of Condensation Ratio for Fast Image Retrieval (영상 검색의 속도 향상을 위한 차원 축소율 최적화)

  • 이세한;이주호;조정원;최병욱
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1515-1518
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    • 2003
  • This paper suggests the condensed two-stage retrieval method for fast image retrieval in the content-based image retrieval system, and proves the validity of the performance. The condensed two-stage retrieval method reduces the overall response time remarkably while it maintains relevance with the conventional exhaustive search method. It is explained by properties of the Cauchy-Schwartz inequality. In experimental result, it turns out that there is an optimal value of condensation ratio which minimizes the overall response time. We analyze the optimal condensation ratio by modeling a similarity computation time mathematically.

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Predictive Direct Torque Control Algorithm for Induction Motors and its Digital Implementation

  • Mutschler, Peter;Flach, Erich
    • Proceedings of the KIPE Conference
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    • 1998.10a
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    • pp.1-6
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    • 1998
  • To achieve fast control action, direct control methods should be used. "Direct Mean Torque Control" (DMTC) combines the good dynamic performance of Direct Torque Control (DTC) with the advantages of inherently constant switching frequency and time equidistant control for implementation in a digital signal processor. Since DMTC is a predictive control algorithm, the model and its correction deserves special investigations. This paper proposes a steady-state Kalman filter which is well suited for fast computation.mputation.

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Improvement of Tomographic Imaging in Coded Aperture System based on Simulated annealing

  • Noritoshi Kitabatake;Chen, Yen-Wei;Zensyo Nakao
    • Proceedings of the IEEK Conference
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    • 2000.07a
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    • pp.425-428
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    • 2000
  • In this paper, we propose a new method based on SA(simulated annealing) with a fast algorithm for 3D image reconstructrion from the coded apereture images. The reconstructed images can be significantly improved by SA and to large computation cost of SA can be significantly reduced by the fast algorithm.

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Fast labeling a1gorithm for the surface defect inspection of Cold Mill Strip (냉연 강판의 개별 흠 분리를 위한 고속 레이블링에 관한 연구)

  • Kim, Kyung-Min;Park, Joo-Jo
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.3056-3059
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    • 2000
  • This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

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A New Approach for Autofocusing in Microscopy

  • Tsomko, Elena;Kim, Hyoung-Joong;Han, Hyoung-Seok
    • 한국정보통신설비학회:학술대회논문집
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    • 2008.08a
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    • pp.186-189
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    • 2008
  • In order to estimate cell images, high-performance electron microscopes are used nowadays. In this paper, we propose a new simple, fast and efficient method for real-time automatic focusing in electron microscopes. The proposed algorithm is based on the prediction-error variance, and demonstrates its feasibility by using extensive experiments. This method is fast, easy to implement, accurate, and not demanding on computation time.

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Parallel Synthesis Algorithm for Layer-based Computer-generated Holograms Using Sparse-field Localization

  • Park, Jongha;Hahn, Joonku;Kim, Hwi
    • Current Optics and Photonics
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    • v.5 no.6
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    • pp.672-679
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    • 2021
  • We propose a high-speed layer-based algorithm for synthesizing computer-generated holograms (CGHs), featuring sparsity-based image segmentation and computational parallelism. The sparsity-based image segmentation of layer-based three-dimensional scenes leads to considerable improvement in the efficiency of CGH computation. The efficiency enhancement of the proposed algorithm is ascribed to the field localization of the fast Fourier transform (FFT), and the consequent reduction of FFT computational complexity.

A Cloud-Edge Collaborative Computing Task Scheduling and Resource Allocation Algorithm for Energy Internet Environment

  • Song, Xin;Wang, Yue;Xie, Zhigang;Xia, Lin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2282-2303
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    • 2021
  • To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

Fast Algorithm for Design of Spiral Inductor using Genetic Algorithm with Distributed Computing (유전 알고리듬과 분산처리기법을 이용한 스파이럴 인덕터의 고속설계 기법)

  • Sa, Ki-Dong;Ahn, Chang-Hoi
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.3
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    • pp.446-452
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    • 2008
  • To design a spiral inductor a genetic algorithm is applied with fast computing technique. For the inductance extraction of the given geometry the fast multipole method is used, also the distributed computing technique using 10 personal computers is introduced for the massive computation of the genetic algorithm. A few important design parameters are used as genes for the optimization in the genetic algorithm. The target function is chosen as mean square error of the inductance at several sampling frequency points. A large-scaled inductor is fabricated and compared with the simulated data.

Fast ROI Detection for Speed up in a CNN based Object Detection

  • Kim, Jin-Sung;Lee, Youhak;Lee, Kyujoong;Lee, Hyuk-Jae
    • Journal of Multimedia Information System
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    • v.6 no.4
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    • pp.203-208
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    • 2019
  • Fast operation of a CNN based object detection is important in many application areas. It is an efficient approach to reduce the size of an input image. However, it is difficult to find an area that includes a target object with minimal computation. This paper proposes a ROI detection method that is fast and robust to noise. The proposed method is not affected by a flicker line noise that is a kind of aliasing between camera and LED light. Fast operation is achieved by using down-sampling efficiently. The accuracy of the proposed ROI detection method is 92.5% and the operation time for a frame with a resolution of 640 × 360 is 0.388msec.

FAST ANDROID IMPLIMENTATION OF MONTE CARLO SIMULATION FOR PRICING EQUITY-LINKED SECURITIES

  • JANG, HANBYEOL;KIM, HYUNDONG;JO, SUBEOM;KIM, HANRIM;LEE, SERI;LEE, JUWON;KIM, JUNSEOK
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.24 no.1
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    • pp.79-84
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    • 2020
  • In this article, we implement a recently developed fast Monte Carlo simulation (MCS) for pricing equity-linked securities (ELS), which is most commonly issued autocallable structured financial derivative in South Korea, on the mobile platform. The fast MCS is based on Brownian bridge technique. Although mobile platform devices are easy to carry around, mobile platform devices are slow in computation compared to desktop computers. Therefore, it is essential to use a fast algorithm for pricing ELS on the mobile platform. The computational results demonstrate the practicability of Android application implementation for pricing ELS.