• Title/Summary/Keyword: input estimation

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Implementation of Object-based Multiview 3D Display Using Adaptive Disparity-based Segmentation

  • Park, Jae-Sung;Kim, Seung-Cheol;Bae, Kyung-Hoon;Kim, Eun-Soo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2005.07b
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    • pp.1615-1618
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    • 2005
  • In this paper, implementation of object-based multiview 3D display using object segmentation and adaptive disparity estimation is proposed and its performance is analyzed by comparison to that of the conventional disparity estimation algorithms. In the proposed algorithm, firstly we can get segmented objects by region growing from input stereoscopic image pair and then, in order to effectively synthesize the intermediate view the matching window size is selected according to the extracted feature value of the input stereo image pair. Also, the matching window size for the intermediate view reconstruction (IVR) is adaptively selected in accordance with the magnitude of the extracted feature value from the input stereo image pair. In addition, some experimental results on the IVR using the proposed algorithm is also discussed and compared with that of the conventional algorithms.

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Estimation and Analysis of MIMO Channel Parameters using the SAGE Algorithm (SAGE 알고리즘을 이용한 MIMO 채널 파라미터 추정과 분석)

  • Kim, Joo-Seok;Yeo, Bong-Gu;Choi, Hong-Rak;Kim, Kyung-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.5
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    • pp.79-84
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    • 2017
  • This paper is a multi-input multi-path (Multiple-input multiple-output: MIMO) using a space-alternating generalized expectation maximization(SAGE) algorithm in the parameter channel and determine the channel estimation performance. Estimated by the algorithm, SAGE time-varying channel environment, the channel parameters estimated from the parameters of the channel measured in the island region 781 of the band in order to compare the performance and compares the original data. This allows you to check the performance of the algorithm SAGE and is highly stable to delay spread (Delay Spread), the diffusion angle of arrival (Arrive of Angular Spread) performance in terms of accuracy down through the SAGE algorithm for estimating a more general calculation parameters.

Input-Output Feedback Linearization of Sensorless IM Drives with Stator and Rotor Resistances Estimation

  • Hajian, Masood;Soltani, Jafar;Markadeh, Gholamreza Arab;Hosseinnia, Saeed
    • Journal of Power Electronics
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    • v.9 no.4
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    • pp.654-666
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    • 2009
  • Direct torque control (DTC) of induction machines (IM) is a well-known strategy of these drives control which has a fast dynamic and a good tracking response. In this paper a nonlinear DTC of speed sensorless IM drives is presented which is based on input-output feedback linearization control theory. The IM model includes iron losses using a speed dependent shunt resistance which is determined through some effective experiments. A stator flux vector is estimated through a simple integrator based on stator voltage equations in the stationary frame. A novel method is introduced for DC offset compensation which is a major problem of AC machines, especially at low speeds. Rotor speed is also determined using a rotor flux sliding-mode (SM) observer which is capable of rotor flux space vector and rotor speed simultaneous estimation. In addition, stator and rotor resistances are estimated using a simple but effective recursive least squares (RLS) method combined with the so-called SM observer. The proposed control idea is experimentally implemented in real time using a FPGA board synchronized with a personal computer (PC). Simulation and experimental results are presented to show the capability and validity of the proposed control method.

Performance Improvement of an Extended Kalman Filter Using Simplified Indirect Inference Method Fuzzy Logic (간편 간접추론 방식의 퍼지논리에 의한 확장 칼만필터의 성능 향상)

  • Chai, Chang-Hyun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.15 no.2
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    • pp.131-138
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    • 2016
  • In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

A completely non-contact recognition system for bridge unit influence line using portable cameras and computer vision

  • Dong, Chuan-Zhi;Bas, Selcuk;Catbas, F. Necati
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.617-630
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    • 2019
  • Currently most of the vision-based structural identification research focus either on structural input (vehicle location) estimation or on structural output (structural displacement and strain responses) estimation. The structural condition assessment at global level just with the vision-based structural output cannot give a normalized response irrespective of the type and/or load configurations of the vehicles. Combining the vision-based structural input and the structural output from non-contact sensors overcomes the disadvantage given above, while reducing cost, time, labor force including cable wiring work. In conventional traffic monitoring, sometimes traffic closure is essential for bridge structures, which may cause other severe problems such as traffic jams and accidents. In this study, a completely non-contact structural identification system is proposed, and the system mainly targets the identification of bridge unit influence line (UIL) under operational traffic. Both the structural input (vehicle location information) and output (displacement responses) are obtained by only using cameras and computer vision techniques. Multiple cameras are synchronized by audio signal pattern recognition. The proposed system is verified with a laboratory experiment on a scaled bridge model under a small moving truck load and a field application on a footbridge on campus under a moving golf cart load. The UILs are successfully identified in both bridge cases. The pedestrian loads are also estimated with the extracted UIL and the predicted weights of pedestrians are observed to be in acceptable ranges.

A Study on Correlation Interference Signal Cancellation Algorithm for Target Estimation in Multi Input Multi Output (다중 입력 다중 출력 배열 시스템에서 목표물 추정을 위한 상관성 간섭신호 제거 알고리즘 연구)

  • Lee, Kwan-Hyeong;Song, Woo-Young;Lee, Myeong-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.1
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    • pp.89-93
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    • 2013
  • This paper is estimating a target direction of arrival with incident to receiver in spatial. This paper presented covariance using constraint matrix to correlation interference signal cancellation in multi input multi output array antennas system. we proposed a target direction of arrival estimation algorithm using cost function and minimum variance method. Through simulation, we were analysis a performance to compare general SPT-LCMV algorithm and proposal algorithm. We showed that proposal algorithm improve more target estimation than general SPT-LCMV algorithm in direction of arrival.

Estimation of BOD in wastewater treatment plant by using different ANN algorithms

  • BAKI, Osman Tugrul;ARAS, Egemen
    • Membrane and Water Treatment
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    • v.9 no.6
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    • pp.455-462
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    • 2018
  • The measurement and monitoring of the biochemical oxygen demand (BOD) play an important role in the planning and operation of wastewater treatment plants. The most basic method for determining biochemical oxygen demand is direct measurement. However, this method is both expensive and takes a long time. A five-day period is required to determine the biochemical oxygen demand. This study has been carried out in a wastewater treatment plant in Turkey (Hurma WWTP) in order to estimate the biochemical oxygen demand a shorter time and with a lower cost. Estimation was performed using artificial neural network (ANN) method. There are three different methods in the training of artificial neural networks, respectively, multi-layered (ML-ANN), teaching learning based algorithm (TLBO-ANN) and artificial bee colony algorithm (ABC-ANN). The input flow (Q), wastewater temperature (t), pH, chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (tP), total nitrogen (tN), and electrical conductivity of wastewater (EC) are used as the input parameters to estimate the BOD. The root mean squared error (RMSE) and the mean absolute error (MAE) values were used in evaluating performance criteria for each model. As a result of the general evaluation, the ML-ANN method provided the best estimation results both training and test series with 0.8924 and 0.8442 determination coefficient, respectively.

Sensitivity of Input Parameters in the Spectral Wave Model

  • Park, Hyo-Bong
    • Journal of Ocean Engineering and Technology
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    • v.23 no.2
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    • pp.28-36
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    • 2009
  • Many researches have been done to define the physical parameters for the wave generation and transformation over a coastal region. However, most of these have been limited to the application of particular conditions, as they are generally too empirical. To yield more reasonable wave estimation using a spectral wave model, it is important to understand how they work for the wave estimation. This study involved a comprehensive sensitivity test against the spectral resolution and the physical source/sink terms of the spectral wave model using SWAN and TOMAWAC, which have the same physical background with several different empirical/theoretical formulations. The tests were conducted for the East Anglian coast, UK, which is characterized by a complex bathymetry due to several shoals and offshore sandbanks. For the quantitative and qualitative evaluation of the models' performance with different input conditions, the wave elements and spectrums predicted at representative sites the East Anglia coast were compared/analyzed. The spectral resolution had no significant effect on the model results, but the lowest resolution on the frequency and direction induced underestimations of the wave height and period. The bottom friction and depth-induced breaking terms produced relatively high variations in the wave prediction, depending on which formulation was applied. The terms for the quadruplet and whitecapping had little effect on the wave estimation, whereas the triads tended to predict shorter and higher waves by energy transferring to higher frequencies.

Hybrid Symbol Offset Estimation Algorithm for MIMO OFDM Systems (MIMO OFDM 시스템을 위한 하이브리드 심볼 옵셋 추정 알고리즘)

  • Jung, Hyeok-Koo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.19 no.4
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    • pp.461-469
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    • 2008
  • This paper proposes a hybrid symbol offset estimation algorithm for MIMO(Multiple Input Multiple Output) OFDM system. As MIMO OFDM systems are multiple transmitter and receiver antenna systems, apart from SISO(Single Input Single Output) system, it is possible to use several combining techniques which are used in multiple receive antenna system. In this paper, we propose hybrid symbol offset estimation algorithms using combining techniques in multiple receive antenna systems, simulate and show the performances in MIMO system environments. The proposed equal gain combining correlation algorithm has better performance 1.8 times in searching the ideal symbol offset rather than the conventional early symbol offset algorithm in severe ISI channel.

Channel Estimation with Orthogonal Code in MIMO System (MIMO 환경에서 직교코드를 이용한 채널추정)

  • Park, Do-Hyun;Kang, Eun-Su;Han, Dong-Seog
    • Journal of Broadcast Engineering
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    • v.16 no.6
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    • pp.927-940
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    • 2011
  • In this paper, we improve a time-domain channel estimation algorithm with multi-input multi-output (MIMO) systems for the next-generation digital television (DTV). The conventional algorithm use orthogonal codes for separating channels from the time-domain orthogonal frequency division multiplexing (OFDM) symbols. However. it has the disadvantage of reduced data-rate because of many pilots. The improved algorithm shows better performance than the conventional one even with reduced number of pilots. The improved algorithm is evaluated by computer simulations.