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We describe how to model an irregularly sampled data sequence as a set of observations from a linear stochastic process, permitting data classification and spectral estimation. The technique is a generalisation of the prediction error approach taken by the Burg and Covariance methods, in that a generalised prediction error energy is minimised with respect to the AR coefficients. Various tests on synthetic...
This paper proposes two novel iterative data-adaptive spectral estimation techniques for blood velocity estimation using medical ultrasound scanners. The techniques make no assumption on the sampling pattern of the emissions or the depth samples, allowing for duplex mode transmissions where B-mode images are interleaved with the Doppler emissions. Furthermore, the techniques are shown, using both...
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