Rahul radhakrishnan (13 resultados)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 228,26
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EUR 232,87
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Condición: As New. Unread book in perfect condition.
Non Gaussian State Estimation and the Maximum Correntropy Approach (Control Theory and Applications)
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Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
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EUR 245,97
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 231,93
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Condición: As New. Unread book in perfect condition.
Non Gaussian State Estimation and the Maximum Correntropy Approach (Control Theory and Applications)
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 244,01
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 235,65
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Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
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EUR 270,19
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
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Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
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EUR 276,69
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HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Non Gaussian State Estimation and the Maximum Correntropy Approach (Control Theory and Applications)
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 275,23
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Condición: New.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 341,26
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Hardcover. Condición: Brand New. 208 pages. 9.18x6.12x9.45 inches. In Stock.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 186,08
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Hardcover. 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.…
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Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
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EUR 180,75
Envío por EUR 43,15Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. 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.…
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 313,86
Envío por EUR 31,90Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. 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.…
