Multidimensional Systems and Signal Processing

, Volume 24, Issue 3, pp 583–598 | Cite as

Multi-dimensional Capon spectral estimation using discrete Zhang neural networks

  • Abderrazak BenchabaneEmail author
  • Abdelhak Bennia
  • Fella Charif
  • Abdelmalik Taleb-Ahmed
Communication Brief


The minimum variance spectral estimator, also known as the Capon spectral estimator, is a high resolution spectral estimator used extensively in practice. In this paper, we derive a novel implementation of a very computationally demanding matched filter-bank based a spectral estimator, namely the multi-dimensional Capon spectral estimator. To avoid the direct computation of the inverse covariance matrix used to estimate the Capon spectrum which can be computationally very expensive, particularly when the dimension of the matrix is large, we propose to use the discrete Zhang neural network for the online covariance matrix inversion. The computational complexity of the proposed algorithm for one-dimensional (1-D), as well as for two-dimensional (2-D) and three-dimensional (3-D) data sequences is lower when a parallel implementation is used.


Multi-dimensional spectral estimation Covariance matrix Capon estimator Discrete Zhang neural network 3-D imaging 


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Abderrazak Benchabane
    • 1
    Email author
  • Abdelhak Bennia
    • 2
  • Fella Charif
    • 1
  • Abdelmalik Taleb-Ahmed
    • 3
  1. 1.Département d’Électronique, Faculté des Sciences et de la Technologie et Sciences de la MatièreUniversité Kasdi MerbahOuarglaAlgeria
  2. 2.Département d’Electronique, Faculté des Sciences de l’ingénieurUniversité Mentouri de ConstantineConstantineAlgeria
  3. 3.Laboratoire LAMIH, FRE CNRS 3304 UVHCUniversité de ValenciennesValenciennesFrance

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