• Title/Summary/Keyword: Parametric Algorithm

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COMPUTING THE HAUSDORFF DISTANCE BETWEEN TWO SETS OF PARAMETRIC CURVES

  • Kim, Ik-Sung;McLean, William
    • Communications of the Korean Mathematical Society
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    • v.28 no.4
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    • pp.833-850
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    • 2013
  • We present an algorithm for computing the Hausdorff distance between two parametric curves in $\mathbb{R}^n$, or more generally between two sets of parametric curves in $\mathbb{R}^n$. During repeated subdivision of the parameter space, we prune subintervals that cannot contain an optimal point. Typically, our algorithm costs O(logM) operations, compared with O(M) operations for a direct, brute-force method, to achieve an accuracy of $O(M^{-1})$.

Test-Generation-Based Fault Detection in Analog VLSI Circuits Using Neural Networks

  • Kalpana, Palanisamy;Gunavathi, Kandasamy
    • ETRI Journal
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    • v.31 no.2
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    • pp.209-214
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    • 2009
  • In this paper, we propose a novel test methodology for the detection of catastrophic and parametric faults present in analog very large scale integration circuits. An automatic test pattern generation algorithm is proposed to generate piece-wise linear (PWL) stimulus using wavelets and a genetic algorithm. The PWL stimulus generated by the test algorithm is used as a test stimulus to the circuit under test. Faults are injected to the circuit under test and the wavelet coefficients obtained from the output response of the circuit. These coefficients are used to train the neural network for fault detection. The proposed method is validated with two IEEE benchmark circuits, namely, an operational amplifier and a state variable filter. This method gives 100% fault coverage for both catastrophic and parametric faults in these circuits.

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Motion Sensing Algorithm for SAR Image Using Pre-Parametric Error Modeling (매개변수 사전 오차 모델링 기법을 이용한 SAR 요동측정 알고리즘)

  • Park, Woo Jung;Park, Yong-gonjong;Lee, Soojeong;Park, Chan Gook;Song, Jong-Hwa;Bae, Chang Sik
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.47 no.8
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    • pp.566-573
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    • 2019
  • In order to obtain high-quality images by motion compensation in the airborne synthetic aperture radar (SAR), accurate motion sensing in image acquisition section is necessary. Especially, reducing relative position error and discontinuity in motion sensing is important. To overcome the problem, we propose a pre-parametric error modeling (P-PEM) algorithm which is a real-time motion sensing algorithm for the airborne SAR in this paper. P-PEM is an extended version of parametric error modeling (PEM) method which is a motion sensing algorithm to mitigate the errors in the previous work. PEM estimates polynomial coefficients of INS error which can be assumed as a polynomial in the short term. Otherwise, P-PEM estimates polynomial coefficients in advance and uses at image acquisition section. Simulation results show that the P-PEM reduces relative position error and discontinuity effectively in real-time.

A Novel Parametric Identification Method Using a Dynamic Encoding Algorithm for Searches (DEAS)

  • Kim, Jong-Wook;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.45.6-45
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    • 2002
  • In this paper, a novel optimization algorithm which searches for the local minima of a given cost function is proposed using the familiar property of a binary string, and is applied to the parametric identification of a continuous-time state equation by the estimation of system parameters as well as initial state values. A simple electrical circuit severs as an example, whose precise identification results show the superiority of the proposed algorithm.

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A Study on the Gradual Differentiation in Parametric Design (패러매트릭 디자인에서의 점진적 조형특성 연구)

  • Kim, Yong-Hak;Ahn, Seong-Mo
    • Korean Institute of Interior Design Journal
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    • v.27 no.2
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    • pp.175-185
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    • 2018
  • The purpose of this study is to analyze the concept of 'Gradual Differentiation' in parametric design in terms of pure model logic and thus describe the distinctive feature from the previous design method. To meet the purpose, it explores external cases like gradual factor identified in natural phenomenon and artworks and define the inherent model principles into "Self-similarity', "Correlation', and 'Temporality' by examining these features in terms of algorithm. Meanwhile, it identified the principle of gradual model representation in parametric design within a single system called 'Attractor System' by applying these three concepts into specific methods of parametric design, and by interpreting the logical structure through the association among 'Attractor', 'Field', and 'Differentiation'. The creative utilization of parameter shows that gradual model process in parametric design does not mean a passive "conversion process" merely replacing natural parameter with algorithm; rather, it refers to an active "generating process" creating new meanings and value. By continuing this process of conceptual understanding and insight, creative perspective and practical ability to interpret parameter can be improved.

A new method for ship inner shell optimization based on parametric technique

  • Yu, Yan-Yun;Lin, Yan;Chen, Ming;Li, Kai
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.7 no.1
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    • pp.142-156
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    • 2015
  • A new method for ship Inner Shell optimization, which is called Parametric Inner Shell Optimization Method (PISOM), is presented in this paper in order to improve both hull performance and design efficiency of transport ship. The foundation of PISOM is the parametric Inner Shell Plate (ISP) model, which is a fully-associative model driven by dimensions. A method to create parametric ISP model is proposed, including geometric primitives, geometric constraints, geometric constraint solving etc. The standard optimization procedure of ship ISP optimization based on parametric ISP model is put forward, and an efficient optimization approach for typical transport ship is developed based on this procedure. This approach takes the section area of ISP and the other dominant parameters as variables, while all the design requirements such as propeller immersion, fore bottom wave slap, bridge visibility, longitudinal strength etc, are made constraints. The optimization objective is maximum volume of cargo oil tanker/cargo hold, and the genetic algorithm is used to solve this optimization model. This method is applied to the optimization of a product oil tanker and a bulk carrier, and it is proved to be effective, highly efficient, and engineering practical.

Fast Intra-Prediction Mode Decision Algorithm for H.264/AVC using Non-parametric Thresholds and Simplified Directional Masks

  • Kim, Young-Ju
    • Journal of information and communication convergence engineering
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    • v.7 no.4
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    • pp.501-506
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    • 2009
  • In the H.264/ AVC video coding standard, the intra-prediction coding with various block sizes offers a considerably high improvement in coding efficiency compared to previous standards. In order to achieve this, H.264/AVC uses the Rate-distortion optimization (RDO) technique to select the best intraprediction mode for a macroblock, and it brings about the drastic increase of the computation complexity of H.264 encoder. To reduce the computation complexity and stabilize the coding performance on visual quality, this paper proposed a fast intra-prediction mode decision algorithm using non-parametric thresholds and simplified directional masks. The use of nonparametric thresholds makes the intra-coding performance not be dependent on types of video sequences and simplified directional masks reduces the compuation loads needed by the calculation of local edge information. Experiment results show that the proposed algorithm is able to reduce more than 55% of the whole encoding time with a negligible loss in PSNR and bitrates and provides the stable performance regardless types of video sequences.

Identification of Interval Model for Parametric Uncertain Systems (파라미터 불확실성 시스템의 구간모델 식별)

  • 김동형;우영태;김영철
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.8
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    • pp.462-470
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    • 2003
  • This paper presents an algorithm of identifying parametric uncertainty by way of an interval model. For a given set of frequency response data from an uncertain linear SISO system of which the upper and the lower bounds of both magnitude and phase responses are represented, the proposed algorithm consists of two main parts: first, the nominal model is identified by using Least Square Estimation (LSE), and then an interval model is constructed by expanding the extremal properties of interval systems, so that tightly enclose the given envelopes within those of interval model. Two numerical examples are given to demonstrate and verify the developed algorithm. The identified interval model can be used for evaluating the worst case performance and stability margins against parametric uncertainty by using some extremal properties on interval systems.

Damage Detection of Truss Structures Using Nonlinear Parametric Projection Filter (비선형 파라메트릭 사영필터에 의한 트러스 구조물의 손상 검출)

  • Mun, Hyo-Jun;Suh, Ill-Gyo
    • Journal of Korean Association for Spatial Structures
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    • v.4 no.2 s.12
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    • pp.73-80
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    • 2004
  • In this paper, a study of damage detection for 2-Dimensional Truss Structures using the parametric projection filter theorr is presented. Many researchers are interested in inverse problem and one of solution procedures for inverse problems that are very effective is the approach using the filtering algorithm in conjunction with numerical solution methods. In filtering algorithm, the Kalman filtering algorithm is well known and have been applied to many kind of inverse problems. In this paper, the Parametric projection filtering in conjunction with structural analysis is applied to the identification of damages in 2-D truss structures. The natural frequency and modes of damaged truss model are adopted as the measurement data. The effectiveness of proposed method is verified through the numerical examples.

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