Blind Identification and Separation of Complex-valued Signals (Hardcover)

Eric Moreau, Tülay Adali

  • 出版商: Wiley
  • 出版日期: 2013-10-07
  • 定價: $1,944
  • 售價: 9.5$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,而源分離則是對系統的逆進行盲目估計。通常使用輸出的不同統計量來進行估計。
本書的作者們在複雜域中考慮了盲目識別和源分離問題,其中可用的統計特性更豐富,包括源(底層組件)的非循環性。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新算法。

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。

關於作者

Eric Moreau是法國圖盧茵大學電氣工程學教授。他的研究興趣涉及統計信號處理、高階統計和矩陣/張量分解,並應用於數據分析、電信和雷達領域。
Tülay Adali是美國馬里蘭大學巴爾的摩縣分校電氣工程學教授,並擔任機器學習信號處理實驗室主任。她的研究興趣涉及統計和自適應信號處理,尤其是非線性和複值信號處理,以及生物醫學數據分析和通信應用。

盲目識別是指僅通過系統的輸出來估計多維系統。源分離涉及對系統的逆進行盲目估計。通常使用輸出的不同統計量來進行估計。
作者們考慮了混合了多個底層信號(稱為源)的多輸入/多輸出(MIMO)系統的盲目估計。他們還考慮了直接估計逆系統以進行源分離的情況。然後,他們描述了與可識別性條件和專用代數算法相關的估計理論。這些算法在很大程度上依賴於將被精確描述的複雜源的(統計和/或時頻)特性。