• 제목/요약/키워드: Over-estimation

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IEEE 802.11 기반 시스템에서 채널추정에 관한 연구 (A study on the Channel Estimation Scheme in IEEE 802.11 Based System)

  • 김한종
    • 디지털융복합연구
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    • 제12권3호
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    • pp.249-254
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    • 2014
  • 무선 랜 시스템은 고속의 데이터를 전송하기 위하여 끊임없이 진화 중이며 통신성능을 향상시키기 위해서는 더욱 정밀한 채널추정이 필수적으로 요구된다. 본 논문에서는 IEEE 802.11 기반 무선 모뎀의 PLCP 구조에서 기존의 긴 훈련심볼만을 이용하여 채널을 추정하는 LS 알고리즘의 성능을 개선하고자 하였다. 48개의 부반송파 중에서 12개의 위치에 짧은 훈련 심볼을 전송하고 있다는 사실을 이용하여 2개의 긴 훈련심볼 뿐만 아니라 하나의 짧은심볼도 함께 사용하여 채널을 추정하는 새로운 LS 추정 알고리즘을 제안하였다. 두 개의 긴 훈련심볼 뿐만 아니라 짧은 훈련 심볼을 이용함으로써 보다 향상된 채널 추정을 제공할 수 있음을 보였으며 제안된 채널 추정알고리즘은 IEEE 802.11p WAVE 차량통신 시스템에도 적용이 가능하리라 생각된다. 또한 학부 및 대학원의 OFDM 관련 채널 추정 교육 시 본 논문의 내용이 유용하게 사용될 수 있을 것이다.

전조등 조도변동에 대한 운전자의 인식연구 : 4. 조도변동 기준 및 평가 알고리즘 개발 (A Study on Driver's Perception over the Change of the Headlamp's Illuminance : 4. Development of the Standard and the Algorithm for Limiting Brightness Change)

  • 김기훈;김현지;안옥희;임태영;민재웅;임준채;강병도;김훈
    • 조명전기설비학회논문지
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    • 제21권10호
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    • pp.13-21
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    • 2007
  • 측정 결과와 분석을 바탕으로 전조등 밝기변화의 한계값과 운전자의 안전성을 고려한 평가 알고리즘을 개발하였다. 심리 평가에 의한 전조등 밝기변화의 한계값은 주관적 평가를 토대로 밝기 변화, 눈 깜박임, 불쾌감 등에 대한 값을 제시하였고, 또한, 시인성 측정에 의한 한계값은 차량을 장애물의 위협 없이 안전하게 정지하기 위한 한계값을 제시하였다.

신체 분절의 연조직 변형을 고려한 관성센서신호 기반의 상대위치 추정 칼만필터 (Relative Position Estimation using Kalman Filter Based on Inertial Sensor Signals Considering Soft Tissue Artifacts of Human Body Segments)

  • 이창준;이정근
    • 센서학회지
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    • 제29권4호
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    • pp.237-242
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    • 2020
  • This paper deals with relative position estimation using a Kalman filter (KF) based on inertial sensors that have been widely used in various biomechanics-related outdoor applications. In previous studies, the relative position is determined using relative orientation and predetermined segment-to-joint (S2J) vectors, which are assumed to be constant. However, because body segments are influenced by soft tissue artifacts (STAs), including the deformation and sliding of the skin over the underlying bone structures, they are not constant, resulting in significant errors during relative position estimation. In this study, relative position estimation was performed using a KF, where the S2J vectors were adopted as time-varying states. The joint constraint and the variations of the S2J vectors were used to develop a measurement model of the proposed KF. Accordingly, the covariance matrix corresponding to the variations of the S2J vectors continuously changed within the ranges of the STA-causing flexion angles. The experimental results of the knee flexion tests showed that the proposed KF decreased the estimation errors in the longitudinal and lateral directions by 8.86 and 17.89 mm, respectively, compared with a conventional approach based on the application of constant S2J vectors.

개선된 유전적 프로그래밍 방법을 이용한 부유식 해양 구조물의 중량 추정 모델 연구 (A Study on Weight Estimation Model of Floating Offshore Structures using Enhanced Genetic Programming Method)

  • 엄태섭;노명일;신현경
    • 대한조선학회논문집
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    • 제52권1호
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    • pp.1-7
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    • 2015
  • The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of direct measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model with the genetic programming was suggested for FPSO. The weight estimation model using genetic programming was established by fixing the independent variables based on this data. In addition, the correlation analysis was performed to make up for the weak points of genetic programming; it is apt to induce over-fitting when the number of data is relatively smaller than that of independent variables. That is, by reducing the number of variables through the analysis of the correlation between the independent variables, the increasing effect in the number of weight data can be expected. The reliability of the developed weight estimation model was within 2% of error rate.

딥 뉴럴 네트워크를 이용한 새로운 리튬이온 배터리의 SOC 추정법 (A Novel SOC Estimation Method for Multiple Number of Lithium Batteries Using Deep Neural Network)

  • Khan, Asad;Ko, Young-hwi;Choi, Woojin
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2019년도 추계학술대회
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    • pp.70-72
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    • 2019
  • For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

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Robust Deep Age Estimation Method Using Artificially Generated Image Set

  • Jang, Jaeyoon;Jeon, Seung-Hyuk;Kim, Jaehong;Yoon, Hosub
    • ETRI Journal
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    • 제39권5호
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    • pp.643-651
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    • 2017
  • Human age estimation is one of the key factors in the field of Human-Robot Interaction/Human-Computer Interaction (HRI/HCI). Owing to the development of deep-learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large-scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep-learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre-trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state-of-the-art performance using the proposed method in the Morph-II dataset and have proven that the proposed method can be used effectively using the Adience dataset.

MRAS 퍼지제어를 이용한 유도전동기 회전자의 시정수 추정 (Time Constant Estimation of Induction Motor rotor using MRAS Fuzzy Control)

  • 이정철;이홍균;정동화;차영두
    • 전력전자학회논문지
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    • 제10권2호
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    • pp.155-161
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    • 2005
  • 본 논문에서는 MRAS 퍼지제어를 이용한 회전자 시정수 추정 기법을 제안한다. 회전자 자속을 추정하는 방법은 기준모델과 적응 회전자 모델을 이용한다 이 두 모델은 MRAS의 형태로 구성되며 두 모델의 오차를 영으로 근접하게 제어한다. 두 모델의 파라미터가 정확하면 동일한 결과를 얻는다. 그러나 회전자 시정수의 추정이 정확하게 이루어지지 않으면 두 회전자 자속의 추정은 서로 다른 각도를 가지게 된다. 두 모델의 오차와 오차 변화분을 입력으로 퍼지 제어기를 이용하여 회전자 시정수를 추정한다.

Online Parameter Estimation for Wireless Power Transfer Systems Using the Tangent of the Reflected Impedance Angle

  • Li, Shufan;Liao, Chenglin;Wang, Lifang
    • Journal of Power Electronics
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    • 제18권1호
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    • pp.300-308
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    • 2018
  • An online estimation method for wireless power transfer (WPT) systems is presented without using any measurement of the secondary side or the load. This parameter estimation method can be applied with a controlling strategy that removes both the receiving terminal controller and the wireless communication. This improves the reliability of the system while reducing its costs and size. In a wireless power transfer system with an LCCL impedance matching circuit under a rectifier load, the actual load value, voltage/current and mutual inductance can be reflected through reflected impedance measuring at the primary side. The proposed method can calculate the phase angle tangent value of the secondary loop circuit impedance via the reflected impedance, which is unrelated to the mutual inductance. Then the load value can be determined based on the relationships between the load value and the secondary loop impedance. After that, the mutual inductance and transfer efficiency can be computed. According to the primary side voltage and current, the load voltage and current can also be detected in real-time. Experiments have verified that high estimation accuracy can be achieved with the proposed method. A single-controller based on the proposed parameter estimation method is established to achieve constant current control over a WPT system.

Inverse active wind load inputs estimation of the multilayer shearing stress structure

  • Chen, Tsung-Chien;Lee, Ming-Hui
    • Wind and Structures
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    • 제11권1호
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    • pp.19-33
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    • 2008
  • This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

Constraint-Combined Adaptive Complementary Filter for Accurate Yaw Estimation in Magnetically Disturbed Environments

  • Jung, Woo Chang;Lee, Jung Keun
    • 센서학회지
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    • 제28권2호
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    • pp.81-87
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    • 2019
  • One of the major issues in inertial and magnetic measurement unit (IMMU)-based 3D orientation estimation is compensation for magnetic disturbances in magnetometer signals, as the magnetic disturbance is a major cause of inaccurate yaw estimation. In the proposed approach, a kinematic constraint is used to provide a measurement equation in addition to the accelerometer and magnetometer signals to mitigate the disturbance effect on the orientation estimation. Although a Kalman filter (KF) is the most popular framework for IMMU-based orientation estimation, a complementary filter (CF) has its own advantages over KF in terms of mathematical simplicity and ease of implementation. Accordingly, this paper introduces a quaternion-based CF with a constraint-combined correction equation. Furthermore, the weight of the constraint relative to the magnetometer signal is adjusted to adapt to magnetic environments to optimally deal with the magnetic disturbance. In the results of our validation experiments, the average and maximum of yaw errors were $1.17^{\circ}$ and $1.65^{\circ}$ from the proposed CF, respectively, and $8.88^{\circ}$ and $14.73^{\circ}$ from the conventional CF, respectively, showing the superiority of the proposed approach.