Blind Source Separation
暫譯: 盲源分離
Yu, Xianchuan, Hu, Dan, Xu, Jindong
- 出版商: Wiley
- 出版日期: 2014-01-07
- 售價: $7,620
- 貴賓價: 9.5 折 $7,239
- 語言: 英文
- 頁數: 416
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1118679849
- ISBN-13: 9781118679845
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相關分類:
Data-mining
海外代購書籍(需單獨結帳)
相關主題
商品描述
A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies
The book presents an overview of Blind Source Separation, a relatively new signal processing method. Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style.
This book offers a general overview of the basics of Blind Source Separation, important solutions and algorithms, and in-depth coverage of applications in image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition fMRI medical image processing, geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition. Firstly, the background and theory basics of blind source separation are introduced, which provides the foundation for the following work. Matrix operation, foundations of probability theory and information theory basics are included here. There follows the fundamental mathematical model and fairly new but relatively established blind source separation algorithms, such as Independent Component Analysis (ICA) and its improved algorithms (Fast ICA, Maximum Likelihood ICA, Overcomplete ICA, Kernel ICA, Flexible ICA, Non-negative ICA, Constrained ICA, Optimised ICA). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix Factorization (NMF). Meanwhile, in-depth cases are presented for each algorithm in order to help the reader understand the algorithm and its application field.
- A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies
- Presents new improved algorithms aimed at different applications, such as image feature extraction, remote sensing image fusion, mixed-pixel decomposition of SAR images, image object recognition, and MRI medical image processing
- With applications in geochemical and geophysical data mining, mineral resources prediction and geoanomalies information recognition
- Written by an expert team with accredited innovations in blind source separation and its applications in natural science
- Accompanying website includes a software system providing codes for most of the algorithms mentioned in the book, enhancing the learning experience
Essential reading for postgraduate students and researchers engaged in the area of signal processing, data mining, image processing and recognition, information, geosciences, life sciences.
商品描述(中文翻譯)
**系統性探索經典與當代盲源分離演算法的實務案例研究**
本書概述了盲源分離(Blind Source Separation),這是一種相對較新的信號處理方法。由於該主題的多學科性,本書的寫作旨在吸引來自不同背景的讀者。理解這些演算法需要基本的數學技能(例如,矩陣代數和概率論基礎),儘管本書以入門和易於理解的風格撰寫。
本書提供了盲源分離的基本概述、重要解決方案和演算法,並深入探討在圖像特徵提取、遙感影像融合、合併像素的合成孔徑雷達(SAR)影像分解、圖像物體識別、功能性磁共振影像(fMRI)醫學影像處理、地球化學和地球物理數據挖掘、礦產資源預測及地異常信息識別等應用中的應用。首先介紹盲源分離的背景和理論基礎,為後續的工作提供基礎。這裡包括矩陣運算、概率論基礎和信息論基礎。接下來介紹基本的數學模型和相對較新的盲源分離演算法,如獨立成分分析(Independent Component Analysis, ICA)及其改進演算法(快速ICA、最大似然ICA、過完備ICA、核ICA、靈活ICA、非負ICA、約束ICA、優化ICA)。本書的最後部分考慮了最近的盲源分離演算法,例如稀疏成分分析(Sparse Component Analysis, SCA)和非負矩陣分解(Non-negative Matrix Factorization, NMF)。同時,為每個演算法提供深入的案例,以幫助讀者理解該演算法及其應用領域。
- 系統性探索經典與當代盲源分離演算法的實務案例研究
- 提出針對不同應用的新改進演算法,如圖像特徵提取、遙感影像融合、合併像素的SAR影像分解、圖像物體識別和MRI醫學影像處理
- 應用於地球化學和地球物理數據挖掘、礦產資源預測及地異常信息識別
- 由在盲源分離及其在自然科學應用方面具有認證創新專家的團隊撰寫
- 附帶網站包括一個軟體系統,提供書中提到的大多數演算法的代碼,增強學習體驗
對於從事信號處理、數據挖掘、圖像處理與識別、信息、地球科學和生命科學領域的研究生和研究人員而言,本書是必讀之作。
作者簡介
Xianchuan Yu, Beijing Normal University, P. R. China
Dan Hu, Beijing Normal University, P. R. China
Jindong Xu, Beijing Normal University, P. R. China
作者簡介(中文翻譯)
余先傳,北京師範大學,中國
胡丹,北京師範大學,中國
徐金東,北京師範大學,中國