Multisensor data fusion using neural networks

dc.contributor.author	Yadaiah, N.
dc.contributor.author	Singh, Lakshman
dc.contributor.author	Bapi, Raju S.
dc.contributor.author	Seshagiri Rao, V.
dc.contributor.author	Deekshatulu, B. L.
dc.contributor.author	Negi, Atul
dc.date.accessioned	2022-03-27T05:53:43Z
dc.date.available	2022-03-27T05:53:43Z
dc.date.issued	2006-01-01
dc.description.abstract	This paper presents a hebbian learning based linear single-layer neural network based measurement fusion of multisensor data. The performance of the proposed unsupervised neural network algorithm is compared with traditional fusion methods based on Kaiman filtering such as measurement fusion and state vector fusion. The experiments have been carried out using multisensor data obtained from different radars. The results demonstrate the viability of the proposed algorithm. © 2006 IEEE.
dc.identifier.citation	IEEE International Conference on Neural Networks - Conference Proceedings
dc.identifier.issn	10987576
dc.identifier.uri	10.1109/ijcnn.2006.246777
dc.identifier.uri	http://ieeexplore.ieee.org/document/1716188/
dc.identifier.uri	https://dspace.uohyd.ac.in/handle/1/8654
dc.title	Multisensor data fusion using neural networks
dc.type	Conference Proceeding. Conference Paper
dspace.entity.type

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