Abstract
Autoregressi ve parametric modelling based on the modified covariancc method has been used to realise spectral estimation in real-time. Previous work has implemented this spectral estimator using genetic algorithms (GAs). The work presented here aims to reduce the execution time of the modified covariance method by exploiting the parallel nature of GAs and by incorporating a heterogeneous node for evaluating the average error function in order to obtain the parameters of the adaptive filter and to calculate the power spectral density. Performance analysis and results with respect to the homogeneous transputer-based implementation are presented. This reveals the effectiveness of the heterogeneous approach.
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