Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 214,87
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 221,83
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 214,74
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 226,53
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Librería: California Books, Miami, FL, Estados Unidos de America
EUR 244,92
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 227,09
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 253,89
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Librería: Revaluation Books, Exeter, Reino Unido
EUR 320,34
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Añadir al carritoHardcover. Condición: Brand New. 208 pages. 9.18x6.12x9.45 inches. In Stock.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1032581972 ISBN 13: 9781032581972
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 177,63
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Añadir al carritoHardcover. Condición: new. Hardcover. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. Features:Reviews well-established non-Gaussian estimation methods including applications of techniques Covers relaxation of gaussian assumption Discusses challenges in formulating non-liner non-Gaussian estimation framework Illustrates the applicability of the algorithms mentioned to real-life problems Explores derivation of non-linear non-Gaussian estimation framework based on maximum correntropy criterion This book is aimed at researchers and graduate students in electrical engineering, robotics, and dynamic systems. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1032581972 ISBN 13: 9781032581972
Librería: CitiRetail, Stevenage, Reino Unido
EUR 174,83
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: new. Hardcover. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. Features:Reviews well-established non-Gaussian estimation methods including applications of techniques Covers relaxation of gaussian assumption Discusses challenges in formulating non-liner non-Gaussian estimation framework Illustrates the applicability of the algorithms mentioned to real-life problems Explores derivation of non-linear non-Gaussian estimation framework based on maximum correntropy criterion This book is aimed at researchers and graduate students in electrical engineering, robotics, and dynamic systems. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 249,90
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Añadir al carritoHRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 256,85
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Añadir al carritoHRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 308,70
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Añadir al carritoBuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1032581972 ISBN 13: 9781032581972
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 360,49
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: new. Hardcover. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. Features:Reviews well-established non-Gaussian estimation methods including applications of techniques Covers relaxation of gaussian assumption Discusses challenges in formulating non-liner non-Gaussian estimation framework Illustrates the applicability of the algorithms mentioned to real-life problems Explores derivation of non-linear non-Gaussian estimation framework based on maximum correntropy criterion This book is aimed at researchers and graduate students in electrical engineering, robotics, and dynamic systems. This monograph aims to present the recent advances in state estimation, in terms of relaxing the conventional assumption that probability densities remain Gaussian. The book explains how MCC is integrated into the conventional Bayesian estimation framework and their implementation to real-life problems. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.