Data Fusion for WSN Using Probabilistic Method and Particle Filter - Couverture souple

Patel, Nilay ; Jaliya, Udaysinh

9786138238058: Data Fusion for WSN Using Probabilistic Method and Particle Filter

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ISBN 10 : 6138238052 ISBN 13 : 9786138238058

Editeur : LAP Lambert Academic Publishing, 2018

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�diteur: LAP Lambert Academic Publishing
Date d'�dition: 2018
Langue: anglais
ISBN 10: 6138238052
ISBN 13: 9786138238058
Reliure: Broch�
Nombre de pages: 76
Coordonn�es du fabricant: non disponible
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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Nilay Patel

Edit� par LAP LAMBERT Academic Publishing Dez 2018, 2018

ISBN 10 : 6138238052 ISBN 13 : 9786138238058

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment. 76 pp. Englisch. N� de r�f. du vendeur 9786138238058

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Patel, Nilay; Jaliya, Udaysinh

Edit� par LAP Lambert Academic Publishing, 2019

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Patel, Nilay; Jaliya, Udaysinh

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Patel, Nilay; Jaliya, Udaysinh

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Nilay Patel|Udaysinh Jaliya

Edit� par LAP LAMBERT Academic Publishing, 2018

ISBN 10 : 6138238052 ISBN 13 : 9786138238058

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Patel NilayNilay Patel is a Lecturer at R.C.Technical Institute and joined academic profession 2016. He has completed post graduation in computer engineering from BVM Engg. College, Anand, Gujarat in 2015 and graduation from CITC, Ch. N� de r�f. du vendeur 385661224

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Data Fusion for WSN Using Probabilistic Method and Particle Filter

Nilay Patel

Edit� par LAP LAMBERT Academic Publishing Dez 2018, 2018

ISBN 10 : 6138238052 ISBN 13 : 9786138238058

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment.Books on Demand GmbH, �berseering 33, 22297 Hamburg 76 pp. Englisch. N� de r�f. du vendeur 9786138238058

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Data Fusion for WSN Using Probabilistic Method and Particle Filter : A technique to reduce your sensor data

Nilay Patel

Edit� par LAP LAMBERT Academic Publishing, 2019

ISBN 10 : 6138238052 ISBN 13 : 9786138238058

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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - We have seen a huge increase in the use and application of a tiny device called a sensor in a number of fields. A single network may consist of many tiny sensors that sense different or same types of data. All the data sensed may vary due to data inaccuracy, inconsistency, incorrectness and imperfect so a method should be developed to get the most accurate and correct result. Data fusion is the approach by which we can get the near correct results. In this work, I have simulated three methods and two algorithms to get the best posterior data. All the methods were simulated and the result shows how one can reduce error from sensed data of sensors and predict future data based on previous data considering types of error possible in an environment. N� de r�f. du vendeur 9786138238058

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