A description is given of the various approaches for computing the impulse response function (IRF) by means of deconvolution of measured pressure and flow waveforms. The techniques are applied to Windkessel model data of the arterial system as well as data obtained from dogs. The methods investigated include (1) direct numerical expansion of the convolution integral and (2) iterative methods which include point-Jacobi and successive relaxation methods. These algorithms are found to be extremely sensitive to the presence of noise in the data and it turns out that the initial value of flow plays a vital role in the computation of the IRF. However, the authors have developed a modified Jacobi iterative method which converges rapidly and is less sensitive to noise and the initial values.
|Original language||English (US)|
|Number of pages||1|
|State||Published - 1985|
All Science Journal Classification (ASJC) codes