Blind Identification and Separation of Complex-valued Signals (Hardcover)
暫譯: 複數值信號的盲識別與分離 (精裝版)

Eric Moreau, Tülay Adali

Blind Identification and Separation of Complex-valued Signals (Hardcover)
  • 出版商: Wiley
  • 出版日期: 2013-10-07
  • 售價: $1,944
  • 貴賓價: 9.5 折 $1,847
  • 語言: 英文
  • 頁數: 112
  • 裝訂: Hardcover
  • ISBN: 1848214596
  • ISBN-13: 9781848214590
  • 相關分類: 電機學 Electric-machinery

    • 立即出貨 (庫存=1)

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商品描述

Blind identification consists of estimating a multi-dimensional system only through the use of its output, and source separation, the blind estimation of the inverse of the system. Estimation is generally carried out using different statistics of the output.
The authors of this book consider the blind identification and source separation problem in the complex-domain, where the available statistical properties are richer and include non-circularity of the sources – underlying components. They define identifiability conditions and present state-of-the-art algorithms that are based on algebraic methods as well as iterative algorithms based on maximum likelihood theory.

Contents

1. Mathematical Preliminaries.
2. Estimation by Joint Diagonalization.
3. Maximum Likelihood ICA.

About the Authors

Eric Moreau is Professor of Electrical Engineering at the University of Toulon, France. His research interests concern statistical signal processing, high order statistics and matrix/tensor decompositions with applications to data analysis, telecommunications and radar.
Tülay Adali is Professor of Electrical Engineering and Director of the Machine Learning for Signal Processing Laboratory at the University of Maryland, Baltimore County, USA. Her research interests concern statistical and adaptive signal processing, with an emphasis on nonlinear and complex-valued signal processing, and applications in biomedical data analysis and communications.

Blind identification consists of estimating a multidimensional system through the use of only its output. Source separation is concerned with the blind estimation of the inverse of the system. The estimation is generally performed by using different statistics of the outputs.
The authors consider the blind estimation of a multiple input/multiple output (MIMO) system that mixes a number of underlying signals of interest called sources. They also consider the case of direct estimation of the inverse system for the purpose of source separation. They then describe the estimation theory associated with the identifiability conditions and dedicated algebraic algorithms. The algorithms depend critically on (statistical and/or time frequency) properties of complex sources that will be precisely described.

商品描述(中文翻譯)

盲目識別是指僅通過系統的輸出來估計多維系統，而源分離則是盲目估計系統的逆。估計通常是通過使用輸出的不同統計量來進行的。

本書的作者考慮了複數域中的盲目識別和源分離問題，在這裡可用的統計特性更為豐富，並包括源的非圓性——潛在組件。他們定義了可識別性條件，並提出了基於代數方法以及基於最大似然理論的迭代算法的最先進算法。

目錄
1. 數學預備知識。
2. 通過聯合對角化進行估計。
3. 最大似然獨立成分分析（ICA）。

關於作者
Eric Moreau是法國圖隆大學的電機工程教授。他的研究興趣包括統計信號處理、高階統計和矩陣/張量分解，應用於數據分析、電信和雷達。

Tülay Adali是美國馬里蘭大學巴爾的摩縣分校的電機工程教授及信號處理機器學習實驗室主任。她的研究興趣包括統計和自適應信號處理，特別強調非線性和複數值信號處理，以及在生物醫學數據分析和通信中的應用。

盲目識別是指僅通過系統的輸出來估計多維系統。源分離則涉及系統逆的盲目估計。估計通常是通過使用輸出的不同統計量來進行的。

作者考慮了多輸入/多輸出（MIMO）系統的盲目估計，該系統混合了多個感興趣的潛在信號，稱為源。他們還考慮了為了源分離而直接估計逆系統的情況。然後，他們描述了與可識別性條件相關的估計理論和專用的代數算法。這些算法在很大程度上依賴於複數源的（統計和/或時間頻率）特性，這些特性將被準確描述。

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