Implementation of a parametric spectral estimator using genetic algorithms

Conventional spectral analysis methods use a FFT on consecutive or overlapping windowed data segments. For Doppler ultrasound signals, this approach suffers from an inadequate frequency resolution due to the time segment duration and the nonstationarity characteristics of the signals. Parametric or model-based estimators can give significant improvements in the time-frequency resolution at the expense of a higher computational complexity. This work describes an approach which implements a parametric spectral estimator method using genetic algorithms (GA´s) in order to find the optimum set of parameters for the adaptive filter that minimises the error function. The aim is to reduce the computational complexity of the conventional algorithm by using the simplicity associated to GA´s. This will allow the implementation of higher order filters, increasing the spectrum resolution, and opening a greater scope for using more complex methods.