Ponencia
Globally convergent Newton algorithms for blind decorrelation
Autor/es | Cruces Álvarez, Sergio Antonio
Cichocki, Andrzej |
Departamento | Universidad de Sevilla. Departamento de Teoría de la Señal y Comunicaciones |
Fecha de publicación | 2003 |
Fecha de depósito | 2022-04-21 |
Publicado en |
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Resumen | This paper presents novel Newton algorithms for the blind
adaptive decorrelation of real and complex processes. They
are globally convergent and exhibit an interesting relation ship with the natural gradient algorithm ... This paper presents novel Newton algorithms for the blind adaptive decorrelation of real and complex processes. They are globally convergent and exhibit an interesting relation ship with the natural gradient algorithm for blind decorre lation and the Goodall learning rule. Indeed, we show that these two later algorithms can be obtained from their New ton decorrelation versions when an exact matrix inversion is replaced by an iterative approximation to it. |
Agencias financiadoras | Comisión Interministerial de Ciencia y Tecnología (CICYT). España |
Identificador del proyecto | TIC2001-0751-C04-04 |
Cita | Cruces Álvarez, S.A. y Cichocki, A. (2003). Globally convergent Newton algorithms for blind decorrelation. En 4th International Symposium on Independent Component Analysis and blind signal separation(ICA2003), April 2003, Nara, Japan. |
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