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Proceedings Paper

New fast algorithm for blind MA-system identification based on higher order cumulants
Author(s): Karl-Dirk Kammeyer; B. Jelonnek
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Paper Abstract

In this paper, a new approach to blind Moving Average system identification is presented. It is derived from a specific algorithm for fast blind equalization (EVA, Eigen Vector Algorithm) published recently. The novel approach leads to a generalized eigenvalue problem and is thus denoted as EVI (Eigen Vector Identification). It will be shown that EVI allows a proper system (channel) estimation on the basis of a relatively small block of data samples. Another crucial property of EVI is its robustness against a system order overfit (this is in contrast to other blind algorithms known so far). Finally the EVI performance will be evaluated in presence of additive gaussian noise; it will be demonstrated by simulation results that the degradation of the channel estimate is very small even with low signal to noise ratios.

Paper Details

Date Published: 28 October 1994
PDF: 12 pages
Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190873
Show Author Affiliations
Karl-Dirk Kammeyer, Technical Univ. of Hamburg-Harburg (Germany)
B. Jelonnek, Technical Univ. of Hamburg-Harburg (Germany)

Published in SPIE Proceedings Vol. 2296:
Advanced Signal Processing: Algorithms, Architectures, and Implementations V
Franklin T. Luk, Editor(s)

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