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Springer An Introduction to Sequential Monte Carlo - Particle Filters

Databases

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Description

Discover the power of Sequential Monte Carlo (SMC) methods with this clear, introductory guide. Designed for students, researchers, and professionals, the book walks you through the core theory behind particle filters and shows how to turn concepts into practical algorithms. Real-world examples span signal processing, epidemiology, machine learning, population ecology, quantitative finance, and robotics, helping you see immediate relevance to your field. Each chapter balances mathematical insight with step-by-step computational tips, so you can implement SMC techniques confidently. Whether you need a solid foundation for academic work or a reliable reference for applied projects, this volume provides the tools to analyze data sequentially and make informed decisions. Written by experts and published by Springer, it offers a comprehensive yet accessible resource that grows with your expertise, from basic principles to advanced applications.

Key Features

Clear explanation of SMC theory makes complex ideas easy to grasp for beginners and seasoned analysts alike.

Step-by-step computational guidance helps you implement particle filters without getting lost in technical details.

Broad range of applications shows how SMC methods solve problems in signal processing, epidemiology, finance, and more.

Comprehensive coverage from foundational concepts to advanced methodology ensures the book grows with your skill level.

Published by Springer, a trusted name in academic publishing, guaranteeing reliable, high-quality content.

Product Specifications

Format: paperback
ASIN: 3030478475
Category: Books > Subjects > Computing & Internet > Databases
Domain: Amazon UK
Release Date: 03 October 2021
Listed Since: 05 September 2021

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Springer An Introduction to Sequential Monte Carlo - Particle Filters

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