• Title/Summary/Keyword: semi-random

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Wireless Power Transfer System using Semi-random Magnetic Field (semi-random 자장을 사용하는 적합한 무선전력전송 시스템)

  • Lim, Dong-Nam;Lee, Dong-Su;Jeon, Seong-Jeub
    • Proceedings of the KIPE Conference
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    • 2014.07a
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    • pp.480-481
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    • 2014
  • In this paper, a feeder system for wireless power transfer is investigated, which generates semi-random magnetic field using three currents with different frequencies. A semi-random field is very useful to magnetizing a pickup irrespective of its posture.

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Wireless Power Transfer System Based on Semi-random Magnetic Flux (준랜덤 자속을 사용하는 무선전력 전송 시스템)

  • Heo, Joon;Jeon, Seong-Jeub
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.8
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    • pp.1222-1229
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    • 2017
  • In this paper, a wireless power transfer system with semi-random magnetic flux is studied. Directions of semi-random magnetic flux are changing almost randomly which can induce voltages at coils irrelevantly to coil's posture. So, very convenient charging is possible. Semi-random magnetic flux can be generated by a coil system which has three coils perpendicular to each other and carrying currents with different frequencies. A prototype for charging mobile devices is constructed and tested, and the proposal is verified.

Semi-Supervised Learning Using Kernel Estimation

  • Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.629-636
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    • 2007
  • A kernel type semi-supervised estimate is proposed. The proposed estimate is based on the penalized least squares loss and the principle of Gaussian Random Fields Model. As a result, we can estimate the label of new unlabeled data without re-computation of the algorithm that is different from the existing transductive semi-supervised learning. Also our estimate is viewed as a general form of Gaussian Random Fields Model. We give experimental evidence suggesting that our estimate is able to use unlabeled data effectively and yields good classification.

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Semi-active bounded optimal control of uncertain nonlinear coupling vehicle system with rotatable inclined supports and MR damper under random road excitation

  • Ying, Z.G.;Yan, G.F.;Ni, Y.Q.
    • Coupled systems mechanics
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    • v.7 no.6
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    • pp.707-729
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    • 2018
  • The semi-active optimal vibration control of nonlinear torsion-bar suspension vehicle systems under random road excitations is an important research subject, and the boundedness of MR dampers and the uncertainty of vehicle systems are necessary to consider. In this paper, the differential equations of motion of the coupling torsion-bar suspension vehicle system with MR damper under random road excitation are derived and then transformed into strongly nonlinear stochastic coupling vibration equations. The dynamical programming equation is derived based on the stochastic dynamical programming principle firstly for the nonlinear stochastic system. The semi-active bounded parametric optimal control law is determined by the programming equation and MR damper dynamics. Then for the uncertain nonlinear stochastic system, the minimax dynamical programming equation is derived based on the minimax stochastic dynamical programming principle. The worst-case disturbances and corresponding semi-active bounded parametric optimal control are obtained from the programming equation under the bounded disturbance constraints and MR damper dynamics. The control strategy for the nonlinear stochastic vibration of the uncertain torsion-bar suspension vehicle system is developed. The good effectiveness of the proposed control is illustrated with numerical results. The control performances for the vehicle system with different bounds of MR damper under different vehicle speeds and random road excitations are discussed.

ON ALMOST SURE CONVERGENCE OF NEGATIVELY SUPERADDITIVE DEPENDENT FOR SEMI-GAUSSIAN RANDOM VARIABLES

  • BAEK, JONG-IL;SEO, HYE-YOUNG
    • Journal of applied mathematics & informatics
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    • v.39 no.1_2
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    • pp.145-153
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    • 2021
  • When {Xni|1 ≤ i ≤ n, n ≥ 1} be an array of rowwise negatively superadditive dependent(NSD) for semi-Gaussian random variables and {ani|1 ≤ i ≤ n, n ≥ 1} is an array of constants, we study the almost sure convergence of weighted sums ∑ni=1 aniXni under some appropriate conditions and we obtain some corollaries.

Sign Language Spotting Based on Semi-Markov Conditional Random Field (세미-마르코프 조건 랜덤 필드 기반의 수화 적출)

  • Cho, Seong-Sik;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.36 no.12
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    • pp.1034-1037
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    • 2009
  • Sign language spotting is the task of detecting the start and end points of signs from continuous data and recognizing the detected signs in the predefined vocabulary. The difficulty with sign language spotting is that instances of signs vary in both motion and shape. Moreover, signs have variable motion in terms of both trajectory and length. Especially, variable sign lengths result in problems with spotting signs in a video sequence, because short signs involve less information and fewer changes than long signs. In this paper, we propose a method for spotting variable lengths signs based on semi-CRF (semi-Markov Conditional Random Field). We performed experiments with ASL (American Sign Language) and KSL (Korean Sign Language) dataset of continuous sign sentences to demonstrate the efficiency of the proposed method. Experimental results show that the proposed method outperforms both HMM and CRF.

Semi-deterministic Sparse Matrix for Low Complexity Compressive Sampling

  • Quan, Lei;Xiao, Song;Xue, Xiao;Lu, Cunbo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.5
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    • pp.2468-2483
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    • 2017
  • The construction of completely random sensing matrices of Compressive Sensing requires a large number of random numbers while that of deterministic sensing operators often needs complex mathematical operations. Thus both of them have difficulty in acquiring large signals efficiently. This paper focuses on the enhancement of the practicability of the structurally random matrices and proposes a semi-deterministic sensing matrix called Partial Kronecker product of Identity and Hadamard (PKIH) matrix. The proposed matrix can be viewed as a sub matrix of a well-structured, sparse, and orthogonal matrix. Only the row index is selected at random and the positions of the entries of each row are determined by a deterministic sequence. Therefore, the PKIH significantly decreases the requirement of random numbers, which has a complex generating algorithm, in matrix construction and further reduces the complexity of sampling. Besides, in order to process large signals, the corresponding fast sampling algorithm is developed, which can be easily parallelized and realized in hardware. Simulation results illustrate that the proposed sensing matrix maintains almost the same performance but with at least 50% less random numbers comparing with the popular sampling matrices. Meanwhile, it saved roughly 15%-35% processing time in comparison to that of the SRM matrices.

Application of Probability Density Function in SFEM and Corresponding Limit Value (추계론적 유한요소해석에서의 확률밀도함수 사용과 수렴치)

  • Noh Hyuk-Chun
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2006.04a
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    • pp.857-864
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    • 2006
  • Due to the difficulties in numerical generation of random fields that satisfy not only the probabilistic distribution but the spectral characteristics as well. it is relatively hard to find an exact response variability of a structural response with a specific random field which has its features in the spatial and spectral domains. In this study. focusing on the fact that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for in-plane and plate bending structures. In this procedure, the probability density function is used directly resulting in a semi-exact solution for the random field in the state of random variable. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density functions.

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Efficient Strategies to Verify VHDL Model (VHDL 모델의 효율적인 검증 방법)

  • 김강철
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.526-529
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    • 2003
  • This paper presents two strategies to refute clock cycles when using stopping rule in VHDL model verification. The first method is that a semi-random variable is defined and the data that stay in the range of semi-random variable are skipped when stopping rule is running. The second one is to keep the old values of parameters when phases are changed. 12 VHDL models are examined to observe the effectiveness of strategies.

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Performance Analysis of Turbo code using Semi Random Interleaver over the Radio Communication Channel (무선통신 채널에서 세미 랜덤 인터리버를 이용한 터보코드의 성능분석)

  • 홍성원
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.5
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    • pp.1067-1075
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    • 2000
  • In this paper, the performance of turbo code using semi random interleaver over the radio communication channel was analyzed. In the result, we proved that the performance of decoder was excellent as increase the interleaver size, constraint length, and iteration number. When the constraint length of turbo code using seim random interleaver and convolutional code is constant, and BER $10^{-4}$ each value of $E_b/N_o$ was 6.4(DB) and 1.7(dB). There(ore, when the constraint length was constant, we proved that the performance of turbo code using semi random interleaver is superior to convolutional code about 4.7(dB) in the case of BER=$10^{-4}$.

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