£196.99

Springer Sequential Monte Carlo Methods in Practice - Springer Book

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Description

This comprehensive guide from Springer covers Sequential Monte Carlo methods, a revolutionary approach for on-line data analysis across diverse industries. The text explores techniques known as bootstrap filters, condensation, optimal Monte Carlo filters, particle filters, and survival of the fittest. These methods enable the numerical solution of complex, non-standard problems that were previously considered intractable, making them essential for professionals in financial modeling, target tracking, and computer vision. The book provides the first complete treatment of these advanced techniques, including detailed convergence results and practical applications. Readers will find valuable insights into tracking, guidance, automated target recognition, and aircraft systems. This used copy is in good condition, offering a reliable resource for students, researchers, and practitioners looking to master these critical statistical tools. The content bridges theoretical foundations with real-world implementation, ensuring a deep understanding of how these filters operate in dynamic environments. Whether you are working on automated systems or analyzing complex data streams, this volume serves as an authoritative reference for modern computational statistics.

Key Features

Comprehensive treatment of Sequential Monte Carlo methods including bootstrap filters and particle filters

Covers convergence results and practical applications in financial modeling and computer vision

Addresses complex non-standard problems previously intractable with traditional numerical methods

Includes specific use cases for tracking, guidance, automated target recognition, and aircraft systems

Published by Springer as part of the Information Science and Statistics series

Used book in good condition, offering reliable access to advanced statistical techniques

Product Specifications

Colour
Yellow
Format
Hardcover
Domain
Amazon UK
Release Date
21 June 2001
Listed Since
12 February 2007

Barcode

No barcode data available

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