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- W2058398772 abstract "Abstract Doppler blood flow spectral estimation is a technique for non-invasive cardiovascular disease detection. Blood flow velocity and disturbance may be determined by measuring the spectral mean frequency and bandwidth, respectively. The work presented here, evaluates a high performance parallel-Doppler Signal Processing architecture (SHARC) for the computation of a parametric model-based spectral estimation method known as the modified covariance algorithm. The model-based method incorporates improvement in frequency resolution when compared with Fast Fourier Transform (FFT)-based methods. However, the computational complexity and the need for real-time response of the algorithm, makes necessary the use of high performance processing in order to fulfil such demands. Sequential and parallel implementations of the algorithm are introduced. A performance analysis of the implementations is also presented, demonstrating the effectiveness of the algorithm and the feasibility for real-time response of the system. The results open a greater scope for utilising this architecture in implementing new and more complex methods. The results are applied to the development of a real-time spectrum analyser for pulsed Doppler blood flow instrumentation." @default.
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- W2058398772 date "1999-11-01" @default.
- W2058398772 modified "2023-10-01" @default.
- W2058398772 title "High performance parallel-DSP computing in model-based spectral estimation" @default.
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- W2058398772 doi "https://doi.org/10.1016/s0141-9331(99)00041-1" @default.
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