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Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
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Añadir al carritoPaperback. Condición: Brand New. 84 pages. 8.66x5.91x0.19 inches. In Stock.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Nov 2017, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -Design of Rectangular Microstrip Patch Antenna based on Artificial Neural Network (ANN) is a concept which can be utilized successfully in designing of microstrip patch antenna. The Microstrip Patch Antenna can be developed in different shapes and due to their many attractive features it has drawn attention of industries and researchers over the past decades for an ultimate solution for wireless communication. The existing era of wireless communication has led to the design of an efficient, wide band, low cost and small volume antennas which can readily be incorporated into a broad spectrum of systems. This needs very accurate calculation of various design parameters. Patch dimensions of Patch antenna is a vital parameter in deciding its utility. The rectangular microstrip antennas are made up with dimensions of width and length over a ground plane with a substrate thickness and dielectric constants. This book exploits the capability of artificial neural networks to calculate the resonating frequency of Rectangular Microstrip Patch Antenna. Since Neural networks have recently gained attention as a fast and flexible vehicle to Electromagnetic modeling, simulations and optimization.Books on Demand GmbH, Überseering 33, 22297 Hamburg 84 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Design of Rectangular Microstrip Patch Antenna Using ANN | A Complete Study Analysis Design and Comparison of various Neural Network Algorithm | Bablu Kumar Singh | Taschenbuch | 84 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9786202059725 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing Nov 2017, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Design of Rectangular Microstrip Patch Antenna based on Artificial Neural Network (ANN) is a concept which can be utilized successfully in designing of microstrip patch antenna. The Microstrip Patch Antenna can be developed in different shapes and due to their many attractive features it has drawn attention of industries and researchers over the past decades for an ultimate solution for wireless communication. The existing era of wireless communication has led to the design of an efficient, wide band, low cost and small volume antennas which can readily be incorporated into a broad spectrum of systems. This needs very accurate calculation of various design parameters. Patch dimensions of Patch antenna is a vital parameter in deciding its utility. The rectangular microstrip antennas are made up with dimensions of width and length over a ground plane with a substrate thickness and dielectric constants. This book exploits the capability of artificial neural networks to calculate the resonating frequency of Rectangular Microstrip Patch Antenna. Since Neural networks have recently gained attention as a fast and flexible vehicle to Electromagnetic modeling, simulations and optimization. 84 pp. Englisch.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
Librería: Majestic Books, Hounslow, Reino Unido
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Singh Bablu KumarBablu Kumar Singh is Associate Professor in Electronics & Communication Engineering at Jodhpur Institute of Engineering & Technology, Rajasthan, India. He earned his Bachelor of Engineering from Rajasthan University.
Idioma: Inglés
Publicado por LAP LAMBERT Academic Publishing, 2017
ISBN 10: 6202059729 ISBN 13: 9786202059725
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 37,20
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Design of Rectangular Microstrip Patch Antenna based on Artificial Neural Network (ANN) is a concept which can be utilized successfully in designing of microstrip patch antenna. The Microstrip Patch Antenna can be developed in different shapes and due to their many attractive features it has drawn attention of industries and researchers over the past decades for an ultimate solution for wireless communication. The existing era of wireless communication has led to the design of an efficient, wide band, low cost and small volume antennas which can readily be incorporated into a broad spectrum of systems. This needs very accurate calculation of various design parameters. Patch dimensions of Patch antenna is a vital parameter in deciding its utility. The rectangular microstrip antennas are made up with dimensions of width and length over a ground plane with a substrate thickness and dielectric constants. This book exploits the capability of artificial neural networks to calculate the resonating frequency of Rectangular Microstrip Patch Antenna. Since Neural networks have recently gained attention as a fast and flexible vehicle to Electromagnetic modeling, simulations and optimization.