Algorithms and Programs of Dynamic Mixture Estimation: Unified Approach to Different Types of Components eBook

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Algorithms and Programs of Dynamic Mixture Estimation
Unified Approach to Different Types of Components
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.

This is a digital product.

Algorithms and Programs of Dynamic Mixture Estimation: Unified Approach to Different Types of Components is written by Ivan Nagy; Evgenia Suzdaleva and published by Springer. The Digital and eTextbook ISBNs for Algorithms and Programs of Dynamic Mixture Estimation are 9783319646718, 3319646710 and the print ISBNs are 9783319646701, 3319646702.