The Data Fusion Method of Redundant Gyroscope System Based on Virtual Gyroscope Technology

Song, Jinlong; Shi, Zhao; Du, Binhan; Han, Lanyi; Wang, Zhiwei; Wang, Huaiguang

doi:10.1109/jsen.2019.2930314

Cited by 21 publications

(6 citation statements)

References 10 publications

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“…There is no uniform standard for selecting member characteristics. The choice of membership feature type is determined by people's overall experience [20].…”

Section: Data Fusion Technologymentioning

confidence: 99%

Corporate Governance Decision-making and Legal Protection Model Based on Data Fusion Technology

2023

acccm

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Corporate governance covers economics, business administration, law, and auditing and information technology. Effective corporate governance decision-making is an important source of a company's competitive advantage, it is one of the decisive factors to improve the competitiveness of an organization, and it plays a key role in ensuring the rapid development of the organization and sustainable growth at the same time. The quality of management is not only related to the company's performance, but also has a significant impact on the efficiency and effectiveness of the company's investment decisions, which in turn has a significant impact on the development of high-tech industries. Therefore, the legal protection of corporate governance decisions is very necessary. Faced with the huge amount of resources on the Internet today, netizens will always have a way to make use of them if they want to. In order to protect company resources and governance decisions, this paper aims to study a set of legal protection models for corporate governance decisions based on data fusion technology, so as to improve the protection of corporate governance decisions, which is conducive to the long-term sustainable development of the company. Using data fusion technology to conduct related experiments, the experimental results of this paper show that it is compared with other algorithms. The efficiency value of the method proposed in this paper can be higher than 95%, and the privacy protection and calculation accuracy are also due to other algorithms, which can have a large application space in corporate governance decision-making and its legal protection model.

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“…There is no uniform standard for selecting member characteristics. The choice of membership feature type is determined by people's overall experience [20].…”

Section: Data Fusion Technologymentioning

confidence: 99%

Corporate Governance Decision-making and Legal Protection Model Based on Data Fusion Technology

2023

acccm

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“…Since the last scales of WV are more variable, we focus on studying the coverage of the confidence intervals based on the coefficients obtained using the SVO method with ω 2 . Indeed, c ω2 is less dependent on the last scales by construction and more on the first scales, which allows to better illustrate the asymptotic properties of the estimated coefficients, whose asymptotic covariance can be approximated by the proposed estimator Σ * given in (8). Since the considered model has a closed-form representation of the WCCV, we can directly compute the matrix A 0 defined in (4) based on ω 2 and therefore obtain the true coefficients c 0 with (6).…”

Section: A Casementioning

confidence: 99%

“…With the aim of addressing the above limitation of MEMS IMUs, increased research has been focused on taking advantage of their small size, cost and power consumption allowing the construction of arrays of such sensors, for instance placing multiple off-the-shelf sensor triads in a planar configuration, or single axis sensors in a non-planar one [8]. Partially redundant observations of the same quantity can be fused to compute synthetic measurements with better stochastic properties compared to those of the single sensors.…”

Section: Introductionmentioning

confidence: 99%

Scale-wise Variance Minimization for Optimal Virtual Signals: An Approach for Redundant Gyroscopes

Zhang¹,

Cucci²,

Molinari³

et al. 2021

Preprint

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The increased use of low-cost gyroscopes within inertial sensors for navigation purposes, among others, has brought to the development of a considerable amount of research in improving their measurement precision. Aside from developing methods that allow to model and account for the deterministic and stochastic components that contribute to the measurement errors of these devices, an approach that has been put forward in recent years is to make use of arrays of such sensors in order to combine their measurements thereby reducing the impact of individual sensor noise. Nevertheless combining these measurements is not straightforward given the complex stochastic nature of these errors and, although some solutions have been suggested, these are limited to certain specific settings which do not allow to achieve solutions in more general and common circumstances. Hence, in this work we put forward a non-parametric method that makes use of the wavelet cross-covariance at different scales to combine the measurements coming from an array of gyroscopes in order to deliver an optimal measurement signal without needing any assumption on the processes underlying the individual error signals. As a result of this work we also study an appropriate non-parametric approach for the estimation of the asymptotic covariance matrix of the wavelet cross-covariance estimator which has important applications beyond the scope of this work. The theoretical properties of the proposed approach are studied and are supported by simulations and real applications, indicating that this method represents an appropriate and general tool for the construction of optimal virtual signals that are particularly relevant for arrays of gyroscopes. Moreover, the results of this work can support the creation of optimal signals for other types of inertial sensors other than gyroscopes as well as for redundant measurements in other domains other than navigation.

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“…In the big data environment, there are three ways to fuse multi-source data, namely, data fusion based on different scenes, data fusion based on feature level, and data fusion based on sematic learning [14]. This paper chooses the data fusion based on different scenes to merge the datasets of different stages and scenes for data mining.…”

Section: Data Processing and Multi-source Fusionmentioning

confidence: 99%

Prediction of English Scores of College Students Based on Multi-source Data Fusion and Social Behavior Analysis

Zhao¹,

Ren²,

Zheng³

2020

RIA

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Multi-source data fusion is the premise of applying big data technology in specific fields. Inspired by the theory on multi-source data fusion, this paper fuses various data on college students, including motion trajectories, consumptions, and social behaviors, and adopts support vector machine (SVM), a machine learning (ML) classifier to predict the English scores of college students. The behavior trajectories were taken into account, because this type of data represents the social similarity between students. Specifically, the behavioral features of college students were extracted, and subject to principal component analysis (PCA). Based on these features, the correlation between student score and social relation was analyzed, and used to predict the English scores of college students. Experimental results show that our method can accurately reflect the relationship between the social behaviors and course scores of college students.

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The Data Fusion Method of Redundant Gyroscope System Based on Virtual Gyroscope Technology

Cited by 21 publications

References 10 publications

Corporate Governance Decision-making and Legal Protection Model Based on Data Fusion Technology

Corporate Governance Decision-making and Legal Protection Model Based on Data Fusion Technology

Scale-wise Variance Minimization for Optimal Virtual Signals: An Approach for Redundant Gyroscopes

Prediction of English Scores of College Students Based on Multi-source Data Fusion and Social Behavior Analysis

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