Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Adaptive Identification of Nonlinear Multiple-Input Multiple-Output Systems Based on Volterra Models
Year:2010
Research Areas
  • Electronics engineering
Information
Abstract
Multiple-input multiple-output systems are increasingly important in a great number of fields, as is the case with telecommunications, robotics, biology, neuroscience, etc. In this paper, Volterra models are applied to a class of MIMO nonlinear systems, showing that linearity with respect to the coefficients ensures the availability of a global solution for the identification problem. The applicability of traditional learning algorithms, as Least-Mean-Square (LMS), is conditioned by eigenvalue spread, mainly dominated by nonlinear effects. This convergence issue and others are shown by means of a theoretical treatment and some examples.
International
Si
Congress
6th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM'10)
960
Place
Ma'ale Hahamisha (Israel)
Reviewers
Si
ISBN/ISSN
978-1-4244-8977-0
Start Date
04/10/2010
End Date
07/10/2010
From page
1
To page
4
Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop
Participants
  • Autor: Angel Fernandez Herrero (UPM)
  • Autor: Carlos Carreras Vaquer (UPM)
  • Autor: Fco. Javier Casajus Quiros (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Aplicaciones del Procesado de Señal (GAPS)
  • Centro o Instituto I+D+i: Centro de Domótica Integral, CEDINT
  • Departamento: Ingeniería Electrónica
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