Classification, Parameter Estimation and State Estimation : An Engineering Approach Using MatLab
暫譯: 分類、參數估計與狀態估計:使用 MatLab 的工程方法
Ferdinand van der Heijden, Robert P. Duin, Dick de Ridder, David M. J. Tax
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商品描述
Description:
Classification, Parameter Estimation and State Estimation is a practical and concise inter-disciplinary guide for data analysts and designers interested in advanced measurement-based systems. Highlighting the practical deployment of theoretical issues, the book provides a useful experimentation platform for skilled engineers to implement and evaluate design concepts.
Features:
- A fully integrated and unified approach to parameter estimation, pattern classification and optimal (state) estimation.
- An introduction to emerging techniques such as support vector machines and particle filtering.
- Implementations in Matlab using the PRTools toolbox, with appendices providing the necessary documentation and useful functions for this and other existing toolboxes.
- End-of-chapter exercises and numerous worked out examples within the text and on the Internet.
A valuable text for students and researchers in engineering, computer science, physics and applied mathematics, this book will also prove an essential reference for the practising civil, control, electrical and mechanical engineer.
Table of Contents:
Preface.
Foreword.
1. Introduction.
2. Detection and Classification.
3. Parameter Estimation.
4. State Estimation.
5. Supervised Learning.
6. Feature Extraction and Selection.
7. Unsupervised Learning.
8. State Estimation in Practice.
9. Worked Out Examples.
Appendix A: Topics Selected from Functional Analysis.
Appendix B: Topics Selected from Linear Algebra and Matrix Theory.
Appendix C: Probability Theory.
Appendix D: Discrete-time Dynamic Systems.
Appendix E: Introduction to PRTools.
Appendix F: Used MATLAB Toolboxes.
Index.
商品描述(中文翻譯)
**描述:**
《分類、參數估計與狀態估計》是一本實用且簡明的跨學科指南,適合對先進的基於測量的系統感興趣的數據分析師和設計師。該書強調理論問題的實際應用,為技術工程師提供了一個有用的實驗平台,以實施和評估設計概念。
**特點:**
- 完全整合且統一的參數估計、模式分類和最佳(狀態)估計的方法。
- 介紹新興技術,如支持向量機(support vector machines)和粒子過濾(particle filtering)。
- 使用PRTools工具箱在Matlab中的實現,附錄提供必要的文檔和其他現有工具箱的有用函數。
- 每章結尾的練習題和文本及互聯網上的多個範例。
這本書對於工程、計算機科學、物理學和應用數學的學生和研究人員來說是一本有價值的教材,對於實踐中的土木、控制、電氣和機械工程師來說也是一本必不可少的參考書。
**目錄:**
- 前言
- 序言
- 1. 介紹
- 2. 偵測與分類
- 3. 參數估計
- 4. 狀態估計
- 5. 監督學習
- 6. 特徵提取與選擇
- 7. 非監督學習
- 8. 實踐中的狀態估計
- 9. 已解範例
- 附錄A:從函數分析中選取的主題
- 附錄B:從線性代數和矩陣理論中選取的主題
- 附錄C:概率論
- 附錄D:離散時間動態系統
- 附錄E:PRTools簡介
- 附錄F:使用的MATLAB工具箱
- 索引