Independent Component Analysis (Hardcover)

Aapo Hyvärinen, Juha Karhunen, Erkki Oja

  • 出版商: Wiley
  • 出版日期: 2001-06-01
  • 售價: $1,387
  • 語言: 英文
  • 頁數: 504
  • 裝訂: Hardcover
  • ISBN: 047140540X
  • ISBN-13: 9780471405405
  • 下單後立即進貨 (約5~7天)

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商品描述

A comprehensive introduction to ICA for students and practitioners

Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more.

Independent Component Analysis is divided into four sections that cover:

  • General mathematical concepts utilized in the book
  • The basic ICA model and its solution
  • Various extensions of the basic ICA model
  • Real-world applications for ICA models

Authors Hyvärinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Table of Contents

Preface.

Introduction.

MATHEMATICAL PRELIMINARIES.

Random Vectors and Independence.

Gradients and Optimization Methods.

Estimation Theory.

Information Theory.

Principal Component Analysis and Whitening.

BASIC INDEPENDENT COMPONENT ANALYSIS.

What is Independent Component Analysis?

ICA by Maximization of Nongaussianity.

ICA by Maximum Likelihood Estimation.

ICA by Minimization of Mutual Information.

ICA by Tensorial Methods.

ICA by Nonlinear Decorrelation and Nonlinear PCA.

Practical Considerations.

Overview and Comparison of Basic ICA Methods.

EXTENSIONS AND RELATED METHODS.

Noisy ICA.

ICA with Overcomplete Bases.

Nonlinear ICA.

Methods using Time Structure.

Convolutive Mixtures and Blind Deconvolution.

Other Extensions.

APPLICATIONS OF ICA.

Feature Extraction by ICA.

Brain Imaging Applications.

Telecommunications.

Other Applications.

References.

Index.

商品描述(中文翻譯)

《獨立成分分析:學生和從業人員的全面介紹》是一本對獨立成分分析(ICA)這一新興技術提供全面介紹的書籍,包含了理解和應用該技術所需的基礎數學背景。這是第一本提供ICA基礎知識、重要解決方案和算法以及圖像處理、電信、音頻信號處理等新應用的綜合性介紹。

《獨立成分分析》分為四個部分,涵蓋了以下內容:

- 本書使用的一般數學概念
- 基本ICA模型及其解決方案
- 基本ICA模型的各種擴展
- ICA模型的實際應用

作者Hyvärinen、Karhunen和Oja在ICA的發展中做出了重要貢獻,本書涵蓋了所有相關理論、新算法和各個領域的應用。研究人員、學生和從業人員可以從這本易於理解且豐富的書籍中獲得幫助和信息。

目錄如下:

前言
引言
數學預備知識
隨機向量和獨立性
梯度和優化方法
估計理論
信息理論
主成分分析和白化
基本獨立成分分析
什麼是獨立成分分析?
通過最大化非高斯性進行ICA
通過最大似然估計進行ICA
通過最小化互信息進行ICA
通過張量方法進行ICA
通過非線性去相關和非線性主成分分析進行ICA
實際考慮因素
基本ICA方法的概述和比較
擴展和相關方法
帶噪聲的ICA
使用超完備基的ICA
非線性ICA
使用時間結構的方法
卷積混合和盲解卷積
其他擴展
ICA的應用
通過ICA進行特徵提取
腦成像應用
電信應用
其他應用
參考文獻
索引