Fuzzy-Integral Based Estimate of Vertical-Direction Error Caused by Pointing Fingers at Objects

2020 ◽  
Vol 24 (3) ◽  
pp. 413-421
Author(s):  
Masayoshi Kanoh ◽  
Tsuyoshi Nakamura ◽  
◽  
Keyword(s):  
Error Estimation ◽  
Vertical Direction ◽  
Observation Point ◽  
Target Point ◽  
Fuzzy Integral ◽  
Estimation Model ◽  
Direction Error ◽  
Finger Position

There have been recent attempts to control home electric appliances and devices using robots. Information can be shared with robots by using finger pointing. Finger pointing is used as a means of communication with people around. However, when a person points at an object with a finger, position of the object cannot be indicated accurately. In this work, we studied the error between a target point, which a person tries to point at with a finger, and an observation point, which is actually pointed at. We also proposed an error estimation model using a fuzzy integral to estimate and correct the error at the observation point.

scholarly journals SAR Observation Error Estimation Based on Maximum Relative Projection Matching

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Y. Zhang ◽  
B. P. Wang ◽  
Y. Fang ◽  
Z. X. Song
Keyword(s):  
Error Estimation ◽  
Estimation Method ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Reconstruction Method ◽  
Observation Error ◽  
Estimation Model ◽  
Reconstruction Process ◽  
Single Observation ◽  
Imaging Results

The existing sparse imaging observation error estimation methods are to usually estimate the error of each observation position by substituting the error parameters into the iterative reconstruction process, which has a huge calculation cost. In this paper, by analysing the relationship between imaging results of single-observation sampling data and error parameters, a SAR observation error estimation method based on maximum relative projection matching is proposed. First, the method estimates the precise position parameters of the reference position by the sparse reconstruction method of joint error parameters. Second, a relative error estimation model is constructed based on the maximum correlation of base-space projection. Finally, the accurate error parameters are estimated by the Broyden–Fletcher–Goldfarb–Shanno method. Simulation and measured data of microwave anechoic chambers show that, compared to the existing methods, the proposed method has higher estimation accuracy, lower noise sensitivity, and higher computational efficiency.

scholarly journals Numerical and Experimental Evaluation of Error Estimation for Two-Way Ranging Methods

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 616 ◽  
Author(s):  
Cung Lian Sang ◽  
Michael Adams ◽  
Timm Hörmann ◽  
Marc Hesse ◽  
Mario Porrmann ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Comparative Analysis ◽  
Error Estimation ◽  
Experimental Evaluation ◽  
Ieee 802.15.4 ◽  
Clock Synchronization ◽  
Estimation Model ◽  
Clock Drift ◽  
Wireless Transceiver ◽  
Accurate Performance

The Two-Way Ranging (TWR) method is commonly used for measuring the distance between two wireless transceiver nodes, especially when clock synchronization between the two nodes is not available. For modeling the time-of-flight (TOF) error between two wireless transceiver nodes in TWR, the existing error model, described in the IEEE 802.15.4-2011 standard, is solely based on clock drift. However, it is inadequate for in-depth comparative analysis between different TWR methods. In this paper, we propose a novel TOF Error Estimation Model (TEEM) for TWR methods. Using the proposed model, we evaluate the comparative analysis between different TWR methods. The analytical results were validated with both numerical simulation and experimental results. Moreover, we demonstrate the pitfalls of the symmetric double-sided TWR (SDS-TWR) method, which is the most highlighted TWR method in the literature because of its highly accurate performance on clock-drift error reduction when reply times are symmetric. We argue that alternative double-sided TWR (AltDS-TWR) outperforms SDS-TWR. The argument was verified with both numerical simulation and experimental evaluation results.

scholarly journals Lateral Flight Technical Error Estimation Model for Performance Based Navigation

2011 ◽  
Vol 24 (3) ◽  
pp. 329-336 ◽  
Author(s):  
Hongsheng ZHAO ◽  
Xiaohao XU ◽  
Jun ZHANG ◽  
Yanbo ZHU ◽  
Chuansen YANG ◽  
...  
Keyword(s):  
Error Estimation ◽  
Technical Error ◽  
Estimation Model ◽  
Performance Based Navigation

Influence Factors Analysis of Oil Depot Valve Internal Leakage Quantitative Inspection Using Acoustic Emission

2014 ◽  
Vol 1030-1032 ◽  
pp. 1318-1322
Author(s):  
Fu Xing Zong ◽  
Ai She Shui ◽  
Hui Wang
Keyword(s):  
Acoustic Emission ◽  
Error Estimation ◽  
Relative Error ◽  
Influence Factors ◽  
Quantitative Model ◽  
Estimation Model ◽  
Factors Analysis ◽  
Main Factors

This paper aims at the oil depot valve internal leakage quantitative inspection using acoustic emission. On the basis of giving the valve internal leakage quantitative model, the main factors which effected quantification of leakage rates are theoretical analyzed and the relative error estimation model is presented. The influence of main factors on the accuracy of leakage quantitative model and the correctness of the relative error estimation model are verified by experiments. Finally, research mentality on how to improve leakage quantitative model is proposed.

scholarly journals Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

2021 ◽  
Author(s):  
Viet Anh Nguyen ◽  
Soroosh Shafieezadeh-Abadeh ◽  
Daniel Kuhn ◽  
Peyman Mohajerin Esfahani
Keyword(s):  
Nash Equilibrium ◽  
Mean Square Error ◽  
Error Estimation ◽  
Estimation Error ◽  
Convex Program ◽  
Mean Square ◽  
Estimation Model ◽  
Mean Square Error Estimation ◽  
Distributionally Robust ◽  
Zero Sum

We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The proposed model can be viewed as a zero-sum game between a statistician choosing an estimator—that is, a measurable function of the observation—and a fictitious adversary choosing a prior—that is, a pair of signal and noise distributions ranging over independent Wasserstein balls—with the goal to minimize and maximize the expected squared estimation error, respectively. We show that, if the Wasserstein balls are centered at normal distributions, then the zero-sum game admits a Nash equilibrium, by which the players’ optimal strategies are given by an affine estimator and a normal prior, respectively. We further prove that this Nash equilibrium can be computed by solving a tractable convex program. Finally, we develop a Frank–Wolfe algorithm that can solve this convex program orders of magnitude faster than state-of-the-art general-purpose solvers. We show that this algorithm enjoys a linear convergence rate and that its direction-finding subproblems can be solved in quasi-closed form.

The Research and Simulation on Optimization Method for Diverse Network Intrusions

2014 ◽  
Vol 556-562 ◽  
pp. 5740-5743
Author(s):  
Feng Kang ◽  
Xiao Ping Zeng ◽  
Xiao Hui Jiang
Keyword(s):  
Complex Network ◽  
Error Estimation ◽  
Detection Method ◽  
Optimization Method ◽  
Experimental Results ◽  
Classification Methods ◽  
Network Environment ◽  
Estimation Model ◽  
Network Intrusions

In current complex network environment, various kinds of attacks are mixed together forming the attack group. The diversity of the attack group leads to diverse attack signatures, which cannot be constrained by uniform conditions. Based on mixed attack signatures estimation model, the paper proposes a detection method for mixed and diverse attack groups. The paper classifies the different attacks in the mixed and diverse attack groups by use of attack constraint classification methods, builds invasion recognition particle tree, and detects mixed diverse attack groups in complex network environment according to error estimation. Experimental results show that the algorithm can effectively improve the accuracy of detection in complex network environment. atures;

Metering equipment running error estimation model based on genetic optimized LM algorithm

2021 ◽  
pp. 1-9
Author(s):  
Liang Chen ◽  
Youpeng Huang ◽  
Tao Lu ◽  
Sanlei Dang ◽  
Zhengmin Kong
Keyword(s):  
Real Time ◽  
Error Estimation ◽  
Electricity Consumption ◽  
Current Method ◽  
Smart Meter ◽  
Estimation Model ◽  
Conservation Of Energy ◽  
Model Based ◽  
Regular Sampling ◽  
Lm Algorithm

The current method of smart meter verification relies on manual regular sampling inspection, which is heavy in workload and poor in real-time, and can’t fully monitor all the equipments. Therefore, a remote real-time error monitoring algorithm is indispensable. We propose a smart meter error estimation model based on genetic optimized Levenberg-Marquarelt (LM) algorithm. Firstly, based on the law of conservation of energy, the relationship between smart meter error and electricity consumption is established. Then, LM algorithm is optimized based on genetic algorithm and used to estimate the operating error of electricity meter. Finally, we used the actual data of the pilot cities in a province for the experiment. The results show that the proposed method can effectively improve the accuracy of smart meter error estimation.

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