• Title/Summary/Keyword: Parameterized

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A C++ Extension based on a Parameterized Dataflow Model for Embedded Streaming Applications (내장형 스트리밍 어플리케이션을 위한 매개변수 데이터플로우 모델 기반의 C++ 확장)

  • Choi, Yoon-Seo;Lin, Yuan
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.4
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    • pp.231-243
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    • 2009
  • Many DSP systems are streaming applications in which streams of data constantly flow through a set of filters. Dataflow programming paradigm is one of effective methods for representing these streaming applications. Dataflow programming model explicitly exposes parallelisms within an application, which helps compiling of the application onto a multicore platform. We propose SPEX(Signal Processing Extension), a language extension to a standard imperative language based on the parameterized dataflow model. Parameterized dataflow model is a kind of dataflow model that can express a modest fashion of dynamism contrary to the synchronous dataflow that can represent only static dataflow. SPEX facilitates characterizing an application written in conventional imperative languages such C/C++ as a streaming application. SPEX is comprised of a few keywords augmented to the conventional C++ syntax for representing dataflow paradigm. SPEX also restricts the syntax and semantics of C++ in order to fit the program within a certain streaming programming category. In this paper, we focus on the capability of SPEX in representing streaming computations within filters and streaming communications among filters.

Bio-Inspired Object Recognition Using Parameterized Metric Learning

  • Li, Xiong;Wang, Bin;Liu, Yuncai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.4
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    • pp.819-833
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    • 2013
  • Computing global features based on local features using a bio-inspired framework has shown promising performance. However, for some tough applications with large intra-class variances, a single local feature is inadequate to represent all the attributes of the images. To integrate the complementary abilities of multiple local features, in this paper we have extended the efficacy of the bio-inspired framework, HMAX, to adapt heterogeneous features for global feature extraction. Given multiple global features, we propose an approach, designated as parameterized metric learning, for high dimensional feature fusion. The fusion parameters are solved by maximizing the canonical correlation with respect to the parameters. Experimental results show that our method achieves significant improvements over the benchmark bio-inspired framework, HMAX, and other related methods on the Caltech dataset, under varying numbers of training samples and feature elements.

Parameterized Simulation Program with Integrated Circuit Emphasis Modeling of Two-level Microbolometer

  • Han, Seung-Oh;Chun, Chang-Hwan;Han, Chang-Suk;Park, Seung-Man
    • Journal of Electrical Engineering and Technology
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    • v.6 no.2
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    • pp.270-274
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    • 2011
  • This paper presents a parameterized simulation program with integrated circuit emphasis (SPICE) model of a two-level microbolometer based on negative-temperature-coefficient thin films, such as vanadium oxide or amorphous silicon. The proposed modeling begins from the electric-thermal analogy and is realized on the SPICE modeling environment. The model consists of parametric components whose parameters are material properties and physical dimensions, and can be used for the fast design study, as well as for the co-design with the readout integrated circuit. The developed model was verified by comparing the obtained results with those from finite element method simulations for three design cases. The thermal conductance and the thermal capacity, key performance parameters of a microbolometer, showed the average difference of only 4.77% and 8.65%, respectively.

The development of a visual tracking system for the stable grasping of a moving object (움직이는 물체의 안정한 Grasping을 위한 시각추적 시스템 개발)

  • 차인혁;손영갑;한창수
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.543-546
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    • 1996
  • We propose a new visual tracking system for grasping which can find grasping points of an unknown polygonal object. We construct the system with the image prediction technique and Extended Kalman Filter algorithm. The Extended Kalman Filter(EKF) based on the SVD can improve the accuracy and processing time for the estimation of the nonlinear state variables. By using it, we can solve the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. The image prediction algorithm can reduce the effect of noise and the image processing time. In the processing of a visual tracking, we can construct the parameterized family and can found the grasping points of unknown object through the geometric properties of the parameterized family.

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Comparision of 3-D Geometrical Modelling of the Lumbar Spine Using Parameterized and Cross-sectional CT Image Reconstruction Method (요추에 있어서 파라미터 기법과 단면CT영상을 이용한 3차원 형상 모델링의 비교)

  • Kim, S.M.;Kim, S.J.;Tack, K.R.;Kim, N.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1998 no.11
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    • pp.159-160
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    • 1998
  • In this study, a three-dimensional geometrical parameterized finite element modeling of the lumbar spine is compared with the 3-D reconstruction model from 2-D CT image. feasibility and accuracy of the parameterized modeling method is evaluated compared with conventional 3-D reconstruction method from 2-D CT image.

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An Advanced Visual Tracking and Stable Grasping Algorithm for a Moving Object (시각센서를 이용한 움직이는 물체의 추적 및 안정된 파지를 위한 알고리즘의 개발)

  • 차인혁;손영갑;한창수
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.6
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    • pp.175-182
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    • 1998
  • An advanced visual tracking and stable grasping algorithm for a moving object is proposed. The stable grasping points for a moving 2D polygonal object are obtained through the visual tracking system with the Kalman filter and image prediction technique. The accuracy and efficiency are improved more than any other prediction algorithms for the tracking of an object. In the processing of a visual tracking. the shape predictors construct the parameterized family and grasp planner find the grasping points of unknown object through the geometric properties of the parameterized family. This algorithm conducts a process of ‘stable grasping and real time tracking’.

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TWO-LAYER MUTI-PARAMETERIZED SCHWARZ ALTERNATING METHOD

  • Kim, Sang-Bae
    • Journal of applied mathematics & informatics
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    • v.9 no.1
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    • pp.101-124
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    • 2002
  • The convergence rate of a numerical procedure barred on Schwarz Alternating Method (SAM) for solving elliptic boundary value problems (BVP's) depends on the selection of the interface conditions applied on the interior boundaries of the overlapping subdomains. It hee been observed that the Robin condition(mixed interface condition), controlled by a parameter, can optimize SAM's convergence rate. Since the convergence rate is very sensitive to the parameter, Tang[17] suggested another interface condition called over-determined interface condition. Based on the over-determined interface condition, we formulate the two-layer multi-parameterized SAM. For the SAM and the one-dimensional elliptic model BVP's, we determine analytically the optimal values of the parameters. For the two-dimensional elliptic BVP's , we also formulate the two-layer multi-parameterized SAM and suggest a choice of multi-parameter to produce good convergence rate .

Implementing Parameterized Modules in an Object-oriented Model with an Notion of Scope (Scope 기능을 갖는 객체 지향 모델에서 파라미터화된 모듈 구현 연구)

  • Gwon, Gi-Hang;Sin, Hyeon-Sam
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.7
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    • pp.2072-2075
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    • 2000
  • While object-oriented models are effective in achieving sharing and code reusability, they unfortunately lack a mechanism for giving scope to objects. We revisit an object-oriented model in which each object can be given a scope. We illustrate the usefulness of this model by showing that it supports the notion of parameterized modules without difficulty.

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Receding horizon controller deign for fuzzy systems with input constraints

  • Jeong, Seung-Cheol;Choi, Doo-Jin;Park, Poo-Gyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.83.4-83
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    • 2002
  • $\bullet$ We present a state-feedback RHC for discrete-time TS fuzzy systems with input constriants. $\bullet$ The controller employ the current and one-step past information on the fuzzy weighting functions. $\bullet$ It is obtained from the finite horizon optimization problem with the invariant ellipsoid constraint $\bullet$ Under parameterized LMI conditions on the terminal weighting matrix $\bullet$ The closed-loop system stability is guaranteed. $\bullet$ The parameterized linear matrix inequalities are relaxed to a finite number of solvable LMIs.

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Parametric Modeling Technique in OPERA-3d Preprocessor (OPERA-3d 전처리기에서의 변수화 모델링 기법)

  • Lim, In-Taek;Lee, Sang-Jin
    • Proceedings of the KIEE Conference
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    • 1998.07a
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    • pp.214-216
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    • 1998
  • Parameterizing a model is one of the most efficient ways of conducting "virtual prototying" i.e. exploring the "What if?" scenario. But it is very difficult to construct parameterized models in commercial based FEM programs, because they usually adopt the mouse inputs in their GUI, which cannot be parameterized. We consolidated a parametric modelling technique in OPERA-3d preprocessor, which is one of world leading electromagnetic analysis programs, by combining the mouse inputs in GUI with it's FORTRAN-based self script command language.

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