Titlebook: Local Food Plants of Brazil; Michelle Cristine Medeiros Jacob,Ulysses Paulino A Book 2021 The Editor(s) (if applicable) and The Author(s),

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Food Composition Data: Edible Plants from the Amazonto them. The Amazon rainforest is a complex biome, endowed with rich biological diversity and inhabited by several indigenous peoples and traditional communities, which results in the existence of an extensive biocultural heritage. Among edible plant species and dietary practices, this diversity als

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Food Composition Data: Edible Plants in Pantanal of the culture of the local human populations and are strategic for their food and nutrition security and food sovereignty. We aim to present nutritional value of the main wild food plant species from the Pantanal that are part of the human diet, are abundant in native plant physiognomies, and have

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n Chapter 10 of the first edition into two sections and combined it with Chapter 8. In its place, a very brief introduction to wavelet analysis is included in Chapter 10. Although the pyramid algorithms for wavelet decompositions and reconstructions are quite different from the Kalman filtering al­

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pters exercises, as well as a section at the end of the bookThis new edition presents a thorough discussion of the mathematical theory and computational schemes of Kalman filtering. The filtering algorithms are derived via different approaches, including a direct method consisting of a series of ele

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Daniela Moura de Oliveira Beltrame,Camila Neves Soares Oliveira,Lidio Coradin derived via different approaches, including a direct method consisting of a series of elementary steps, and an indirect method based on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering for time-invariant syste

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Fernanda L. B. Mügge,Sarah M. S. Prates,Juliana de Paula-Souza,Maria G. L. Brandãoative-free higher-order approximation of a Gaussian distribution rather than approximating a non-linear function. Applying the UT to a Kalman-filter-type estimator leads to the well-known unscented Kalman filter (UKF). In general, the UKF works well in Gaussian noises, and its performance may, howev

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Fillipe de Oliveira Pereira,Francinalva Dantas de Medeiros,Patrícia Lima Araújotheoretic quantities (e.g., entropy or correntropy) estimated directly from the data instead of the usual second-order statistical measures, such as variance and covariance, as the optimization costs. In ITL, the correntropy is a local similarity measure (only concerns about the local part of the er

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niques and a wealth of novel results.Can serve as either a rThis book addresses a key technology for digital information processing: Kalman filtering, which is generally considered to be one of the greatest discoveries of the 20th century. It introduces readers to issues concerning various uncertain