• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.19-29
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• 2002

Decentralized filtering for a formation flight instrumentation system by INS/GPS integration is considered in this paper. An elaborate tuning method of the measurement noise covariance is suggested to compensate modeling errors caused by decentralizing the extended Kalman filter. It does not require large data transfer between formation vehicles. Covariance analysis exhibits the superior performance of the proposed approach when compared with the existent decentralized filter and the global filter, which has the target-filter performance.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.2
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• pp.256-264
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• 1996

In this paper, the decentralized suboptimal H$_{2}$ filtering problem is considered. An additional term is added to the centralized optimal H$_{2}$ filter so that the whole filter is decentralized. We derive a necessary and sufficient condition for existence of proposed decentralized filters By employing the solution procedure for the exact model matching problem, we obtain a set of decentralized H$_{2}$ filters, and choose a suboptimal filter from this set of decentralized H$_{2}$ filters.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.418-422
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• 2016

A filtering algorithm based on the decentralized moving average Kalman filter with uncertainties is proposed in this paper. The proposed filtering algorithm presented combines the Kalman filter with the moving average strategy. A decentralized fusion algorithm with the weighted sum structure is applied to the local moving average Kalman filters (LMAKFs) of different window lengths. The proposed algorithm has a parallel structure and allows parallel processing of observations. Hence, it is more reliable than the centralized algorithm when some sensors become faulty. Moreover, the choice of the moving average strategy makes the proposed algorithm robust against linear discrete-time dynamic model uncertainties. The derivation of the error cross-covariances between the LMAKFs is the key idea of studied. The application of the proposed decentralized fusion filter to dynamic systems within a multisensor environment demonstrates its high accuracy and computational efficiency.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.323-325
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• 1993

In this paper, the decentralized suboptimal $H_2$ filtering problem is considered. An additional term is added to the centralized optimal $H_2$ filter so that the whole filter is decentralized. We derive a sufficient condition for existence of such decentralized filters. By employing the solution procedure for the exact model matching problem, we obtain a set of decentralized $H_2$ filters, and choose a suboptimal filter from this set of decentralized $H_2$ filters. Naturally the resulting filter is guaranteed to be stable.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.735-746
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• 1999

We design the robust and inherently fault tolerant decetralized$$H^infty$$ filter for the multisensor state estimation problem when there are insufficient priori informations on the statistical properties of external disturbances. For developing the proposed algorithm, an alternative form of suboptimal$$H^infty$$ filter equations are formulated by applying an alternative form of Kalman filter equations to the indefinite inner product space state model of suboptimal$$H^infty$$ filtering problems. The decentralized$$H^infty$$ filter that consists of local and central fusion filters can be designed effciently using the proposed alternative$$H^infty$$ filiter gain equations. The proposed decentralized$$H^infty$$ filter is robust against un-known external disturbances since it bounds the maximum energy gain from the external disturbances to the estimation errors under the prescribed level$$r^2$$ in both local and central fusion filters and is also fault tolerant due to its inherent redundancy. In addition, the central fusion equations between the global and local data can reduce the unnecessary calculation burden effectively. Computer simulations are made to ceritfy the robustness and fault tolerance of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2072-2079
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• 1998

In this paper, we propose a new decorrelating detector called pseudo-inverse-filtering type decorrelating detector for asynchronous CDMA channels. We first show that the matched filtering and decorrelating operations of the existing decorrelating detectors can be replaced with the pseudo-inverse filtering operations in synchronous channels, and using this fact we show that the decorrelating detector has the largest SNR among the linear detectors that can eliminate MAI. Then we introduce asynchronous pseudo-inverse filtering type decorrelating detector by extending this result for asynchronous channels, and discuss implementation methods of the proposed decorrelating detectors. Since the proposed scheme employs a decentralized structure for updating coefficients, it has the flexibility to add/remove users. Finally we analyze the performance of the proposed decorrelating detector in terms of the bit error rate, and examine its performance improvements over the conventional detectors through computer simulations.

• Journal of the Korea Society of Computer and Information
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• v.5 no.2
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• pp.43-49
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• 2000

The World Wide Web has become a vast information resource where virtually any information can be found. There is a pressing need for appropriate Web search tools due to the very vastness of information space, the rate of growth, and the volatility of data. The agent technology has been studied to address these issues and led to the creation of an adaptive, Proactive. personalized search tools. This study looks into the mechanism of collaborative filtering of information and suggests a decentralized collaborating agents model for information discovery.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.129-142
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• 2019

The interest in the blockchain technology has been increasing since its inception and it has been applied to many fields and sectors. The blockchain technology creates a decentralized environment where no third party controls the data and transaction. Mobile apps recommendation has been extensively used to recommend apps to mobile users. For example, Android-based recommendation applications have been developed to recommend other mobile apps for download depending on user's preferences and mobile context. These recommendations help users discover apps by referring to the experiences of other users. Due to the collection of a large amount of data and user information, there is a problem of insecurity and user's privacy that are prone to be attacked. To address this issue the blockchain technology can be incorporated to assure cryptographic safety. In this paper, we present a survey of the on-going mobile app recommendations and e-commerce technology trend to address how the blockchain can be incorporated into the collaborative filtering recommendation systems to enable the users to set up a secured data, which implies the importance of user privacy preference on personalized app recommendations.