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DC Field | Value | Language |
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dc.contributor.author | Gupta, Saurav | - |
dc.contributor.author | Sahoo, Ajit Kumar | - |
dc.contributor.author | Sahoo, Upendra Kumar | - |
dc.date.accessioned | 2018-12-31T05:08:36Z | - |
dc.date.available | 2018-12-31T05:08:36Z | - |
dc.date.issued | 2018-12 | - |
dc.identifier.citation | 15th IEEE India Council International conference ( INDICON 2018 ), Coimbatore, India, 16-18 December, 2018 | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/3143 | - |
dc.description | Copyright of this document belongs to proceedings publisher. | en_US |
dc.description.abstract | The distributed estimation over wireless sensor networks (WSNs), as opposed to least-squares and fusion-center based estimations, is proficient to work with real-time applications. In this paper, a block-structured Wiener model is identified in a distributed fashion by minimizing the least-squares cost function on prediction error. As the block-structured Wiener model can approximate a large class of nonlinear systems with a small number of characteristics parameters hence makes it more suitable to work with. The global minimization task is reformed into several constrained subtasks in a manner that each node in WSN can obtain the parameters of interest locally. Each node in the network has the ability to combine its local estimates with the single-hop neighbors’ estimates to obtain the global parameters of interest. The optimization of the reformulated cost is accomplished using a powerful distributed method called alternating direction method of multipliers. Simulations are carried on an infinite-order nonlinear system under the impact of observation noise. The obtained results are juxtaposed to the results of non-cooperative algorithm to show the effectiveness and superiority of the proposed algorithm. | en_US |
dc.subject | WSN | en_US |
dc.subject | Nonlinear systems | en_US |
dc.subject | Distributed | en_US |
dc.subject | Basis functions | en_US |
dc.subject | ADMM | en_US |
dc.subject | Fusion-center | en_US |
dc.title | ADMM-Based Distributed Recursive Identification of Wiener Nonlinear Systems Using WSNs | en_US |
dc.type | Article | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2018_INDICON_SGupta_ADMMBased.pdf | Conference paper | 284.18 kB | Adobe PDF | View/Open |
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