Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/5871
Título: High performance parallel-DSP computing in model-based spectral estimation
Autor: Gonzalez, J. S.
Nocetti, D. F. G.
Ruano, M. Graca
Palavras-chave: High performance computing
Parallel processing
Signal processing
Spectral estimation
Doppler ultrasound
Data: 29-Nov-1999
Editora: Elsevier
Resumo: 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. (C) 1999 Elsevier Science B.V. All rights reserved.
Peer review: yes
URI: http://hdl.handle.net/10400.1/5871
DOI: http://dx.doi.org/10.1016/S0141-9331(99)00041-1
ISSN: 0141-9331
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)



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