• 제목/요약/키워드: Machine Computation

검색결과 296건 처리시간 0.024초

하드웨어 유전자 알고리즘을 이용한 무어 머신의 복제 (The clone of Moore machine using hardware genetic algorithm)

  • 서기성;박세현;권혁수;이정환;노석호
    • 한국정보통신학회논문지
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    • 제6권5호
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    • pp.718-723
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    • 2002
  • 본 논문은 무어 머신을 복제하는 새로운 진화 하드웨어를 제안하였다. 제안된 진화 하드웨어는 FPGA 상에서 효과적인 파이프라인, 병렬처리와 Handshaking을 구현했다. 유전자 알고리즘은 다양한 응용 분야의 NP 문제를 해결하는 방법으로 알려져 있으나 긴 계산 시간이 요구되기 때문에 하드웨어 유전자 알고리즘이 최근 관심사가 되고 있다. 기존의 하드웨어 유전자 알고리즘은 고정 길이의 염색체를 사용하지만 제안된 진화 하드웨어는 가변 길이의 염색체를 사용한다. 실험 결과는 제안된 진화 하드웨어가 무어 머신을 복제하는데 있어 적합함을 알 수 있다.

Binary Image Based Fast DoG Filter Using Zero-Dimensional Convolution and State Machine LUTs

  • Lee, Seung-Jun;Lee, Kye-Shin;Kim, Byung-Gyu
    • Journal of Multimedia Information System
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    • 제5권2호
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    • pp.131-138
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    • 2018
  • This work describes a binary image based fast Difference of Gaussian (DoG) filter using zero-dimensional (0-d) convolution and state machine look up tables (LUTs) for image and video stitching hardware platforms. The proposed approach for using binary images to obtain DoG filtering can significantly reduce the data size compared to conventional gray scale based DoG filters, yet binary images still preserve the key features of the image such as contours, edges, and corners. Furthermore, the binary image based DoG filtering can be realized with zero-dimensional convolution and state machine LUTs which eliminates the major portion of the adder and multiplier blocks that are generally used in conventional DoG filter hardware engines. This enables fast computation time along with the data size reduction which can lead to compact and low power image and video stitching hardware blocks. The proposed DoG filter using binary images has been implemented with a FPGA (Altera DE2-115), and the results have been verified.

비디오 감시 시스템을 위한 멀티코어 프로세서 기반의 병렬 SVM (Multicore Processor based Parallel SVM for Video Surveillance System)

  • 김희곤;이성주;정용화;박대희;이한성
    • 정보보호학회논문지
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    • 제21권6호
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    • pp.161-169
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    • 2011
  • 최근 지능형 비디오 감시 시스템은 영상 분석 및 인식기술 등의 보다 진화된 기술 개발을 요구하고 있다. 특히, 비디오 영상에서 객체를 식별하기 위하여 Support Vector Machine(SVM)과 같은 기계학습 알고리즘이 이용된다. 그러나 SVM은 대용량의 데이터를 학습시키기 위하여 많은 계산량이 필요하기 때문에 수행시간을 효율적으로 감소시키기 위하여 병렬처리 기법을 적용할 필요가 있다. 본 논문에서는, 최근 사용이 증가하고 있는 멀티코어 프로세서를 활용한 SVM 학습의 병렬처리 방법을 제안한다. 4-코어 프로세서를 이용한 실험 결과, 제안 방법은 SVM 학습의 순차처리 방법과 비교하여 2.5배 정도 수행시간이 감소됨을 확인하였다.

통합자동생산시스템에서 최적운영방안 결정을 위한 유전자 알고리즘의 개발 (A genetic algorithm for determining the optimal operating policies in an integrated- automated manufacturing system)

  • 임준목
    • 한국산업정보학회논문지
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    • 제4권2호
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    • pp.62-72
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    • 1999
  • 본 논문에서는 자동창고시스템과 자재취급시스템이 통합된 통합자동생산시스템의 하나인 DIO가공시스템을 고려한다. DIO가공시스템에서는 스태커크레인이 가공물의 저장을 위한 운반은 물론 각 기계 사이의 가공물 운반역할을 담당하게 된다. 이러한 시스템에서 일어날 수 있는 문제로 크게 시스템 설계와 관련된 문제와 시스템운영과 관련된 문제로 구분하고 본 논문에서는 시스템의 운영정책에 관련된 문제만을 다룬다. 시스템의 운영과 관련된 문제로는 가공물투입순서, 가공물의 저장위치, 스태커크레인의 작업배정, 가공물선택 등으로 크게 4가지로 나누어서 고려한다. 각각의 운영정책에 대해서 기존의 연구결과로부터 DIO가공시스템의 특성을 반영하는 몇 가지씩의 운영정책을 대안으로 제시하고 최적의 운영정책 결정을 위한 방법론으로 컴퓨터시뮬레이션과 유전자알고리즘을 통합한 방법론을 제시한다. 또한 실험을 통해서 기존의 연구결과와 비교 검토함으로서 제시된 알고리즘의 우수성을 검증한다.

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AN ASSESSMENT OF PARALLEL PRECONDITIONERS FOR THE INTERIOR SPARSE GENERALIZED EIGENVALUE PROBLEMS BY CG-TYPE METHODS ON AN IBM REGATTA MACHINE

  • Ma, Sang-Back;Jang, Ho-Jong
    • Journal of applied mathematics & informatics
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    • 제25권1_2호
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    • pp.435-443
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    • 2007
  • Computing the interior spectrum of large sparse generalized eigenvalue problems $Ax\;=\;{\lambda}Bx$, where A and b are large sparse and SPD(Symmetric Positive Definite), is often required in areas such as structural mechanics and quantum chemistry, to name a few. Recently, CG-type methods have been found useful and hence, very amenable to parallel computation for very large problems. Also, as in the case of linear systems proper choice of preconditioning is known to accelerate the rate of convergence. After the smallest eigenpair is found we use the orthogonal deflation technique to find the next m-1 eigenvalues, which is also suitable for parallelization. This offers advantages over Jacobi-Davidson methods with partial shifts, which requires re-computation of preconditioner matrx with new shifts. We consider as preconditioners Incomplete LU(ILU)(0) in two variants, ever-relaxation(SOR), and Point-symmetric SOR(SSOR). We set m to be 5. We conducted our experiments on matrices from discretizations of partial differential equations by finite difference method. The generated matrices has dimensions up to 4 million and total number of processors are 32. MPI(Message Passing Interface) library was used for interprocessor communications. Our results show that in general the Multi-Color ILU(0) gives the best performance.

에스 브이 엠을 이용한 화자인증 알고리즘의 하드웨어 구현 연구 (A Hardware Implementation of Support Vector Machines for Speaker Verification System)

  • 최우용;황병희;이경희;반성범;정용화;정상화
    • 대한전자공학회논문지SP
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    • 제41권3호
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    • pp.175-182
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    • 2004
  • 화자인증이란 생체인식 방법 중의 하나로 사람의 목소리를 이용하여 사용자를 인증하는 방법이다. 현재까지 가장 많이 사용되는 화자인증 알고리즘으로는 HMM(Hidden Markov Model)과 DTW(Dynamic Time Warping)를 들 수 있는데, 이들 알고리즘은 사용자의 등록 및 인증을 위해 많은 수의 특징벡터를 필요로 하므로 스마트 카드와 같은 메모리가 제한된 시스템에는 적용하기 어려운 단점이 있다. 본 논문에서는 SVM(Support vector Machine)을 이용함으로써 적은 양의 메모리와 적은 계산량으로 화자인증을 수행할 수 있는 방법을 제안하였으며, 이의 실시간 처리를 위해 하드웨어 구조를 제시하였다. 한국어 4연숫자 데이터베이스를 이용하여 제안한 알고리즘의 성능을 평가한 결과, 기존 알고리즘에 비해 약간의 에러율 증가가 있었으나 수행시간 및 모델크기에서는 상당한 감소를 나타내었다. SVM을 이용한 화자인증 알고리즘을 하드웨어로 구현한 결과, 소프트웨어로 구현한 경우에 비해서 훈련시간은 175분의 1, 인증시간에서는 6분의 1의 감소를 나타내었다.

산업용 로봇 매니퓰레이터의 오프라인 영상피드백 제어 (011-line Visual Feedback Control of Industrial Robot Manipulator)

  • 신행봉;정동연;김용태;이종두;이강두
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2002년도 춘계학술대회 논문집
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    • pp.567-572
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    • 2002
  • The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS ). We can save much efforts and time in adjusting robots to newly defined workcells by using Off-Line Programming System. A proposed visual calibration scheme is based on position-based visual feedback. The visual calibration system is composed of a personal computer, an image processing board, a video monitor, and one camera. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test, and construction of simple silhouette figures. Then, camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection, which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

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로봇 매니퓰레이터의 오프라인 영상피드백 제어 (Off-line Visual Feedback Control of Robot Manipulator)

  • 신행봉;정동연;이종두;이강두;한성현
    • 한국공작기계학회:학술대회논문집
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    • 한국공작기계학회 2001년도 추계학술대회(한국공작기계학회)
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    • pp.140-145
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    • 2001
  • The equipment of industrial robot in manufacturing and assembly lines has rapidly increased. In order to achieve high productivity and flexibility, it becomes very important to develop the visual feedback control system with Off-Line Programming System(OLPS). We can save much efforts and time in adjusting robots to newly defined workcells by using Off-Line Programming System. A proposed visual calibration scheme is based on position-based visual feedback. The visual calibration system is composed of a personal computer, an image processing board, a video monitor, and one camera. The calibration program firstly generates predicted images of objects in an assumed end-effector position. The process to generate predicted images consists of projection to screen-coordinates, visible range test, and construction of simple silhouette figures. Then, camera images acquired are compared with predicted ones for updating position and orientation data. Computation of error is very simple because the scheme is based on perspective projection, which can be also expanded to experimental results. Computation time can be extremely reduced because the proposed method does not require the precise calculation of tree-dimensional object data and image Jacobian.

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Manhole Cover Detection from Natural Scene Based on Imaging Environment Perception

  • Liu, Haoting;Yan, Beibei;Wang, Wei;Li, Xin;Guo, Zhenhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권10호
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    • pp.5095-5111
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    • 2019
  • A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

인공지능 프로세서 기술 동향 (AI Processor Technology Trends)

  • 권영수
    • 전자통신동향분석
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    • 제33권5호
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    • pp.121-134
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    • 2018
  • The Von Neumann based architecture of the modern computer has dominated the computing industry for the past 50 years, sparking the digital revolution and propelling us into today's information age. Recent research focus and market trends have shown significant effort toward the advancement and application of artificial intelligence technologies. Although artificial intelligence has been studied for decades since the Turing machine was first introduced, the field has recently emerged into the spotlight thanks to remarkable milestones such as AlexNet-CNN and Alpha-Go, whose neural-network based deep learning methods have achieved a ground-breaking performance superior to existing recognition, classification, and decision algorithms. Unprecedented results in a wide variety of applications (drones, autonomous driving, robots, stock markets, computer vision, voice, and so on) have signaled the beginning of a golden age for artificial intelligence after 40 years of relative dormancy. Algorithmic research continues to progress at a breath-taking pace as evidenced by the rate of new neural networks being announced. However, traditional Von Neumann based architectures have proven to be inadequate in terms of computation power, and inherently inefficient in their processing of vastly parallel computations, which is a characteristic of deep neural networks. Consequently, global conglomerates such as Intel, Huawei, and Google, as well as large domestic corporations and fabless companies are developing dedicated semiconductor chips customized for artificial intelligence computations. The AI Processor Research Laboratory at ETRI is focusing on the research and development of super low-power AI processor chips. In this article, we present the current trends in computation platform, parallel processing, AI processor, and super-threaded AI processor research being conducted at ETRI.