• Title/Summary/Keyword: Propagated errors

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Stabilization Position Control of a Ball-Beam System Using Neural Networks Controller (신경회로망 제어기을 이용한 볼-빔 시스템의 안정화 위치제어)

  • 탁한호;추연규
    • Journal of the Korean Institute of Navigation
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    • v.23 no.3
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    • pp.35-44
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    • 1999
  • This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

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An Adaptive Estimation Model for Propagation Errors Incurred by CD in FD-CD Transcoding (FD-CD 트랜스코딩기법에서 CD에 의한 전파 왜곡의 적응적 예측 모델)

  • Kim Jin-soo;Kim Jae-Gon
    • Journal of Korea Multimedia Society
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    • v.7 no.11
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    • pp.1571-1579
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    • 2004
  • Recently, FD(Frame Dropping)-CD(Coefficient Dropping) transcoding is considered mainly due to the low computational complexity and simple implementation. But, CD errors in the FD-CD transtoding scheme tend to be propagated and they have a significant effect on the qualities of decoded images. In this paper, we derive the error characteristics incurred by the CD operations and propose an effective estimation model that adaptively describes well the characteristics of propagation/accumulation errors in compressed domain. Furthermore, we apply the proposed model to distortion control achieving nearly constant distortion allocation among frames. Simulation results show that the proposed model is quite accurate in estimating the overall distortions and is effectively applied to distortion control over a range of sequences with varying scene types.

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The Bearing Estimation of Narrowband Acoustic Signals Using DIFAR Beamforming Algorithm (DIFAR 빔형성 알고리듬을 이용한 협대역 음향신호의 방향성 추정)

  • 장덕홍;박홍배;정문섭;김인수
    • Journal of the Korea Institute of Military Science and Technology
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    • v.5 no.2
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    • pp.169-184
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    • 2002
  • In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

Spatio-Temporal Error Concealment of I-frame using GOP structure of MPEG-2 (MPEG-2의 GOP 구조를 이용한 I 프레임의 시공간적 오류 은닉)

  • Kang, Min-Jung;Ryu, Chul
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.1C
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    • pp.72-82
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    • 2004
  • This paper proposes more robust error concealment techniques (ECTs) for MPEG-2 intra coded frame. MPEG-2 source coding algorithm is very sensitive to transmission errors due to the use of variable-length coding. The transmission errors are corrected by error correction scheme, however, they cannot be revised properly. Error concealment (EC) is used to conceal the errors which are not corrected by error correction and to provide minimum visual distortion at the decoder. If errors are generated in intra coded frame, that is the starting frame of GOP, they are propagated to other inter coded frames due to the nature of motion compensated prediction coding. Such propagation of error may cause severe visual distortion. The proposed algorithm in this paper utilizes the spatio-temporal information of neighboring inter coded frames to conceal the successive slices errors occurred in I-frame. The proposed method also overcomes the problems that previous ECTs reside. The proposed algorithm generates consistent performance even in network where the violent transmission errors frequently occur. Algorithm is performed in MPEG-2 video codec and we can confirm that the proposed algorithm provides less visible distortion and higher PSNR than other approaches through simulations.

Development of a neural network method for measuring the energy spectrum of a pulsed electron beam, based on Bremsstrahlung X-Ray

  • Sohrabi, Mohsen;Ayoobian, Navid;Shirani, Babak
    • Nuclear Engineering and Technology
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    • v.53 no.1
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    • pp.266-272
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    • 2021
  • In the pulsed electron beam generators, such as plasma focus devices and linear induction accelerators whose electron pulse width is in the range of nanosecond and less, as well as in cases where there is no direct access to electron beam, like runaway electrons in Tokamaks, measurement of the electron energy spectrum is a technical challenge. In such cases, the indirect measurement of the electron spectrum by using the bremsstrahlung radiation spectrum associated with it, is an appropriate solution. The problem with this method is that the matrix equation between the two spectrums is an ill-conditioned equation, which results in errors of the measured X-ray spectrum to be propagated with a large coefficient in the estimated electron spectrum. In this study, a method based on the neural network and the MCNP code is presented and evaluated to recover the electron spectrum from the X-ray generated by collision of the electron beam with a target. Multilayer perceptron network showed good accuracy in electron spectrum recovery, so that for the X-ray spectrum with errors of 3% and 10%, the network estimated the electron spectrum with an average standard error of 8% and 11%, on all of the energy intervals.

Sensorless Vector Control of Induction Motor Using Neural Networks (신경망을 이용한 유도전동기 센서리스 벡터제어)

  • Park, Seong-Wook;Choi, Jong-Woo;Kim, Heung-Geun;Seo, Bo-Hyeok
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.53 no.4
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    • pp.195-200
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    • 2004
  • Many kinds of speed sensorless control system of induction motor had been developed. But it is difficult to implement at the real system because of complex algorithm and equations. This paper investigates a novel speed sensorless control of induction motor using neural networks. The proposed control strategy is based on neural networks using stator current and output of neural model based on state observer. The errors between the stator current and the output of neural model are back-propagated to adjust the rotor speed, so that adaptive state variable will coincide with the desired state variable. This algorithm may overcome several shortages of conventional model, such as integrator problems, small EMF at low speed and relatively large sensitivity of stator resistance variation. Also, this paper presents a newly developed optimal equation about the momentum constant and the learning rate. The proposed algorithms are verified through simulation.

MONTE CARLO ANALYSIS FOR FIRST ACQUISITION AND TRACKING OF THE KOMPSAT SPACECRAFT

  • Lee, Byeong-Seon;Lee, Jeong-Sook
    • Journal of Astronomy and Space Sciences
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    • v.15 no.2
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    • pp.417-425
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    • 1998
  • Monte Carlo analysis is performed for the first acquisition and tracking of the KOMP-SAT spacecrat in GSOC tracking station after separation from Taurus launch vehicle. The error bounds in position and velocity vector in Earth-fixed coordinate system at injection point are assumed based on the previous launch mission. Ten thousands injection orbital elements with normal distribution are generated and propagated for Monte Carlo analysis. The tracking antenna pointing errors at spacecraft rising time and closest approach time at German Space Operations Center(GSOC) Weiheim track-ing station are derived. Then the tracking antenna scanning angles are analyzed for acquisition and tracking of the KOMPSAT signal.

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Speakers' Intention Analysis Based on Partial Learning of a Shared Layer in a Convolutional Neural Network (Convolutional Neural Network에서 공유 계층의 부분 학습에 기반 한 화자 의도 분석)

  • Kim, Minkyoung;Kim, Harksoo
    • Journal of KIISE
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    • v.44 no.12
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    • pp.1252-1257
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    • 2017
  • In dialogues, speakers' intentions can be represented by sets of an emotion, a speech act, and a predicator. Therefore, dialogue systems should capture and process these implied characteristics of utterances. Many previous studies have considered such determination as independent classification problems, but others have showed them to be associated with each other. In this paper, we propose an integrated model that simultaneously determines emotions, speech acts, and predicators using a convolution neural network. The proposed model consists of a particular abstraction layer, mutually independent informations of these characteristics are abstracted. In the shared abstraction layer, combinations of the independent information is abstracted. During training, errors of emotions, errors of speech acts, and errors of predicators are partially back-propagated through the layers. In the experiments, the proposed integrated model showed better performances (2%p in emotion determination, 11%p in speech act determination, and 3%p in predicator determination) than independent determination models.

A Robust Scheme for Emergency Message Delivery in Vehicle Communications on Freeway (고속도로상의 차량간 통신에서 에러에 강한 긴급메시지 전달 기법)

  • Park, Jeong-Seo;Park, Tae-Keun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.12A
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    • pp.1113-1121
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    • 2010
  • The Vehicle Safety Communications (VSC) is one of VANET applications for preventing vehicle accidents, and it utilizes vehicle-to-vehicle communication to exchange emergency messages. To propagate such messages in VSC, several schemes based on selective flooding have been proposed. Their common idea is that an emergency message is relayed by one of vehicles receiving the message. However, the schemes do not consider the transmission errors and duplications of an emergency event. In the schemes, if there are transmission errors and a vehicle detects a hazard, there may be vehicles which fail to receive an emergency message. If k vehicles detect a hazard, k emergency messages are created and propagated. The duplications of an event increase reliability of the message delivery but decrease efficiency. In this paper, we propose an emergency message delivery scheme which is efficient and robust to transmission errors. Our proposed scheme utilizes clustering for massage aggregation and retransmissions in a cluster. It also uses an acknowledgment mechanism for reliable inter-cluster communication. Our simulation results show that the proposed scheme outperforms Least Common Neighbor Flooding which is one of the selective flooding schemes.

Accuracy of the Loran-C Fix in Cheju Areas (제주지역에서의 Loran-C 위치의 정도)

  • Kim, Gwang-Hong;Sim, Hyeong-Il;Jang, Chung-Sik
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.21 no.2
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    • pp.123-130
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    • 1985
  • This paper was conducted for the purpose of evaluating the accuracy of the observed time difference in Loran-C when the ground wave propagated on the surface included both land sea. The time difference of X and Y station in North East Pacific Chain GRI 5970 was measured at 25 points in Cheju areas. The results obtained are as follows: (1) The errors of time difference for M-X pair are increased when the Loran-C wave propagates above 500m heights of Hanla mountain on propagation path between the observed point and master or X, Y slave station. (2) The errors of time difference for M-X pair are able to decrease by way of correction for the propagation velocity and the geodetic datum, but errors of the time difference for M-Y pair very irregularly because irregular terrain include in propagation path from X station and propagation path from Y station is twice longer than X station. (3) It is confirmed that accuracy of Loran-C fix can elevate by the way of all correction for a geodetic datum transformation, the propagation velocity with refractive index of radio wave and the propagation velocity over land.

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