Adaptive blind MIMO system identification using Principal Component neural models

Konstantinos I. Diamantaras, Athina P. Petropulu

Research output: Contribution to conferencePaperpeer-review


We treat the blind identification problem for a n×n MIMO system using second order frequency-domain statistics and Asymmetric PCA neural models. It is assumed that the source signals are colored, stationary, and pair-wise independent sequences with otherwise unknown statistics. We introduce a set of invariant indices that are used to tackle the problem of frequency-dependent ambiguities in the ordering and the phase of the retrieved singular vectors. For the case of 2×2 systems we present a complete identification procedure based on the corresponding invariant indices and we conjecture that these indices will be instrumental in the solution of the general n×n problem as well.

Original languageEnglish (US)
Number of pages5
StatePublished - 1999
Externally publishedYes
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: Jul 10 1999Jul 16 1999


OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence


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