Bayesian Signal Processing: Classical, Modern, and Particle Filtering Methods (Adaptive and Cognitive Dynamic Systems: Signal Processing, Learning, Communications and Control)

James V. Candy

  • 出版商: Wiley
  • 出版日期: 2016-07-12
  • 定價: $4,400
  • 售價: 9.0$3,960
  • 語言: 英文
  • 頁數: 640
  • 裝訂: Hardcover
  • ISBN: 1119125456
  • ISBN-13: 9781119125457
  • 相關分類: 機率統計學 Probability-and-statistics
  • 立即出貨 (庫存=1)

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商品描述

Presents the Bayesian approach to statistical signal processing for a variety of useful model sets 

This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems.

The second edition of Bayesian Signal Processing features: 

  • “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters
  • Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems
  • Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics
  • New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving
  • MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available
  • Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian 

Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.

商品描述(中文翻譯)

本書介紹了貝葉斯統計信號處理方法,適用於各種有用的模型集。

本書旨在從基礎知識(貝葉斯定理)開始,提供讀者一個統一的貝葉斯處理方法,進一步發展到更高級的模型為基礎的技術(序列蒙特卡羅抽樣)。這本新版書籍增加了一章關於“序列貝葉斯檢測”,一節關於“集合卡爾曼濾波器”,以及擴展了案例研究,詳細介紹了各種應用的貝葉斯解決方案。這些研究展示了貝葉斯方法應用於現實世界問題的粒子濾波器設計、自適應粒子濾波器和序列貝葉斯檢測器。除了這些重大發展外,還擴展了一些章節,以填補第一版的空白。這些擴展包括粒子濾波器(PF)設計的度量標準,強調傳統的“合理性測試”,並將集合技術作為性能分析的基本要求。對信息理論度量標準的擴展及其在PF設計中的應用得到了充分的發展和應用。這些書籍的擴展已經更新,以提供更具連貫性的貝葉斯處理討論,並通過示例和應用使讀者理解解決估計/檢測問題的替代方法。

《貝葉斯信號處理第二版》的特點包括:

- 線性、線性化和非線性系統的“傳統”卡爾曼濾波器;“現代”無香濾波器和集合卡爾曼濾波器;以及“下一代”貝葉斯粒子濾波器。
- 序列貝葉斯檢測技術,包括基於模型的方案,用於各種現實世界問題。
- 實用的貝葉斯處理器設計,包括從簡單的合理性測試和集合技術到複雜的信息度量的全面性能分析方法。
- 詳細介紹了自適應粒子濾波和序列貝葉斯檢測的新案例研究,展示了應用問題解決的更多貝葉斯方法。
- 每章末尾的MATLAB®筆記幫助讀者使用現成的軟件命令解決複雜問題,並指出其他可用的軟件包。
- 包含問題集,以測試讀者的知識,並幫助他們將新技能應用到實踐中。

《信號處理第二版》適用於所有研究和應用信號處理於日常問題的學生、科學家和工程師。