• Title/Summary/Keyword: Test vector

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Vibration Filter Using Vector Channel Periodic Lattice

  • Hwang, Won-Gul;Im, Hyung-Eun
    • Journal of Mechanical Science and Technology
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    • v.20 no.12
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    • pp.2043-2051
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    • 2006
  • This paper considered identification of vibration characteristics of flexible structure with vector channel periodic lattice filter. We present an algorithm for AR coefficients for the vector-channel lattice filters, and characteristic equation and transfer function are derived from these coefficients. Vibration lattice filter is then constructed from the vector channel lattice filter, and performance of this vibration filter is tested with a test signal which is a combination of many sine waves to compare the performance of scalar and vector channel lattice. Also it is applied to the cantilever data to identify properties of the system, such as natural frequencies and damping ratios, to show its performance.

Power Quality Disturbances Identification Method Based on Novel Hybrid Kernel Function

  • Zhao, Liquan;Gai, Meijiao
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.422-432
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    • 2019
  • A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

Novel Testing Method of CMOS Operation Amplifier using Offset Voltage (오프셋 전압을 이용한 CMOS 연산 증폭기의 새로운 테스팅 기법)

  • 한석붕;윤원효
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.507-510
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    • 1998
  • In this paper, a novel test method is proposed to detect hard and soft fault in CMOS operational amplifiers. Proposed test method mark use of the offset character, which is one of the op-amps characteristics. During the test mode, CUT is implemented to unit gain op-amps with feedback loop. When the input is grounded, a good circuit has a small offset voltage, but a faulty circuit has a large offset voltage exceeding predefined range of tolerance. Using the proposed method, no test vector is required to be applied. Therefore the test vector generation problem is eliminated and the test time is reduced. The accuracy and effectiveness of the method is verified through HSPICE simulation.

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Sequential Fault Detection and Isolation for Redundant Inertial Sensor Systems with Uncertain Factors

  • Kim, Jeong-Yong;Yang, Cheol-Kwan;Shim, Duk-Sun
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2594-2599
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    • 2003
  • We consider some problems of the Modified SPRT(Sequential Probability Ratio Test) method for fault detection and isolation of inertial redundant sensor systems and propose an Advanced SPRT method to solve the problems of the Modified SPRT method. One problem of the Modified SPRT method to apply to inertial sensor system comes from the effect of inertial sensor errors such as misalignment, scale factor error and sensor bias in the parity vector, which make the Modified SPRT method hard to be applicable. The other problem is due to the correlation of parity vector components which may induce false alarm. We use a two-stage Kalman filter to remove effects of the inertial sensor errors and propose the modified parity vector and the controlled parity vector which removes the effect of correlation of parity vector components. The Advanced SPRT method is derived form the modified parity vector and the controlled parity vector. Some simulation results are presented to show the usefulness of the Advanced SPRT method to redundant inertial sensor systems.

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Improving Code Coverage for the FPGA Based Nuclear Power Plant Controller (FPGA기반 원전용 제어기 코드커버리지 개선)

  • Heo, Hyung-Suk;Oh, Seungrohk;Kim, Kyuchull
    • Journal of IKEEE
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    • v.18 no.3
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    • pp.305-312
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    • 2014
  • IIt takes a lot of time and needs the workloads to verify the RTL code used in complex system like a nuclear control system which is required high level reliability using simple testbench. UVM has a layered testbench architecture and it is easy to modify the testbench to improve the code coverage. A test vector can be easily constructed in the UVM, since a constrained random test vector can be used even though the construction of testbench using UVM. We showed that the UVM testbench is easier than the verilog testbench for the analysis and improvement of code coverage.

Test Vector Generator of timing simulation for 224-bit ECDSA hardware (224비트 ECDSA 하드웨어 시간 시뮬레이션을 위한 테스트벡터 생성기)

  • Kim, Tae Hun;Jung, Seok Won
    • Journal of Internet of Things and Convergence
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    • v.1 no.1
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    • pp.33-38
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    • 2015
  • Hardware are developed in various architecture. It is necessary to verifying value of variables in modules generated in each clock cycles for timing simulation. In this paper, a test vector generator in software type generates test vectors for timing simulation of 224-bit ECDSA hardware modules in developing stage. It provides test vectors with GUI format and text file format.

Vectorization of an Explicit Finite Element Method on Memory-to-Memory Type Vector Computer (Memory-to-Memory방식 벡터컴퓨터에서의 외연적 유한요소법의 벡터화)

  • 이지호;이재석
    • Computational Structural Engineering
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    • v.4 no.1
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    • pp.95-108
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    • 1991
  • An explicit finite element method can be executed more rapidly and effectively on vector computer than on the scalar computer because it has suitable structures for vector processing. In this paper, an efficient vectorization method of the explicit finite element program on the memory-to-memory type vector computer is proposed. First, the general vectorization method which can be applied regardless of the vector architecture is investigated, then the method which is suitable for the memory-to-memory type vector computer is proposed. To illustrate the usefulness of the proposed vectorization method, DYNA3D, the existing explicit finite element program, is migrated on HDS AS/XL V50 which is the memory-to-memory type vector computer. Performance results on actual test show a vector/scalar speedup is above 2.4.

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Adult Image Filtering using Support Vector Mchine (Support Vector Machine을 이용한 유해 이미지 분류)

  • Song, Chull-Hwan;Yoo, Seong-Joon
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.10c
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    • pp.218-221
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    • 2006
  • 본 논문은 인터넷의 대표적인 문제점중의 하나인 Adult Image 분류 연구에 대해 기술한다. 특히 우리는 이러한 Adult Image를 분류하기 위한 Data Set을 5가지 타입으로 구성한다. 이러한 각 Image에 대해 Color, Gradient, Edge Direction 특성의 Feature들을 추출하고 이를 Histogram으로 구성한다. 이렇게 구성된 Histogram을 Support Vector Machine에 적용하여 Adult Image를 분류한다. 그 결과, 우리는 8250개의 Test Set에 대하여 Recall(96.53%), Precision(97.33%), False Positive(2.96%), F-Measure(96.93%)의 성능 결과를 보여준다.

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Forecasting Exchange Rates using Support Vector Machine Regression

  • Chen, Shi-Yi;Jeong, Ki-Ho
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.155-163
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    • 2005
  • This paper applies Support Vector Regression (SVR) to estimate and forecast nonlinear autoregressive integrated (ARI) model of the daily exchange rates of four currencies (Swiss Francs, Indian Rupees, South Korean Won and Philippines Pesos) against U.S. dollar. The forecasting abilities of SVR are compared with linear ARI model which is estimated by OLS. Sensitivity of SVR results are also examined to kernel type and other free parameters. Empirical findings are in favor of SVR. SVR method forecasts exchange rate level better than linear ARI model and also has superior ability in forecasting the exchange rates direction in short test phase but has similar performance with OLS when forecasting the turning points in long test phase.

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Quantitative Structure Activity Relationship Prediction of Oral Bioavailabilities Using Support Vector Machine

  • Fatemi, Mohammad Hossein;Fadaei, Fatemeh
    • Journal of the Korean Chemical Society
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    • v.58 no.6
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    • pp.543-552
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    • 2014
  • A quantitative structure activity relationship (QSAR) study is performed for modeling and prediction of oral bioavailabilities of 216 diverse set of drugs. After calculation and screening of molecular descriptors, linear and nonlinear models were developed by using multiple linear regression (MLR), artificial neural network (ANN), support vector machine (SVM) and random forest (RF) techniques. Comparison between statistical parameters of these models indicates the suitability of SVM over other models. The root mean square errors of SVM model were 5.933 and 4.934 for training and test sets, respectively. Robustness and reliability of the developed SVM model was evaluated by performing of leave many out cross validation test, which produces the statistic of $Q^2_{SVM}=0.603$ and SPRESS = 7.902. Moreover, the chemical applicability domains of model were determined via leverage approach. The results of this study revealed the applicability of QSAR approach by using SVM in prediction of oral bioavailability of drugs.