Artboard 33Artboard 16Artboard 18Artboard 13Artboard 42Artboard 21Artboard 4Artboard 5Artboard 45Artboard 22Artboard 7Artboard 42Artboard 23Artboard 12Artboard 28Artboard 17?Artboard 28Artboard 43Artboard 49Artboard 47Artboard 15Artboard 32Artboard 6Artboard 22Artboard 5Artboard 25Artboard 1Artboard 42Artboard 11Artboard 41Artboard 11Artboard 23Artboard 10Artboard 4Artboard 9Artboard 6Artboard 8Artboard 7Artboard 3Artboard 12Artboard 25Artboard 34Artboard 43Artboard 44Artboard 16Artboard 24Artboard 13Artboard 5Artboard 24Artboard 31Artboard 1Artboard 12Artboard 27Artboard 30Artboard 36Artboard 44Artboard 9Artboard 17Artboard 6Artboard 27Artboard 30Artboard 29Artboard 26Artboard 2Artboard 20Artboard 35Artboard 15Artboard 14Artboard 50Artboard 26Artboard 14Artboard 40Artboard 21Artboard 10Artboard 37Artboard 46Artboard 33Artboard 8
e-book

Bayesian Estimation and Tracking (Cód: 9286588)

Haug,Anton J.

Wiley (Digital)

Ooops! Este produto não está mais a venda.
Mas não se preocupe, temos uma versão atualizada para você.

Ooopss! Este produto está fora de linha, mas temos outras opções para você.
Veja nossas sugestões abaixo!

R$ 182,50

em até 6x de R$ 30,42 sem juros

Total:

Em até 1x sem juros de


Crédito:
Boleto:
Cartão Saraiva:

Total:

Em até 6x sem juros de


Bayesian Estimation and Tracking

R$182,50

Descrição

A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand. Case studies are employed to showcase applications of the discussed topics. In addition, the book supplies block diagrams for each algorithm, allowing readers to develop their own MATLAB® toolbox of estimation methods. Bayesian Estimation and Tracking is an excellent book for courses on estimation and tracking methods at the graduate level. The book also serves as a valuable reference for research scientists, mathematicians, and engineers seeking a deeper understanding of the topics.

Características

Peso 0.00 Kg
Produto sob encomenda Não
Marca Wiley (Digital)
Idioma 337
Acabamento e-book
Territorialidade Internacional
Formato Livro Digital Epub
Gratuito Não
Proteção Drm Sim
Início da Venda 04/01/2016
Código do Formato Epub
Cód. Barras 9781118287804
Número da edição 1
Ano da Publicação 112
AutorHaug,Anton J.