Multichannel Blind Deconvolution of the Arterial Pressure using Ito Calculus Method
Keywords:
FInite Impulse Response (FIR), Multichannel Blind Deconvolution (MBD), Stochastic Calculus (SC)Abstract
Multichannel Blind Deconvolution (MBD) is a powerful tool particularly for the identification and estimation of dynamical systems in which a sensor, for measuring the input, is difficult to place. This paper presents Ito calculus method for the estimation of the known time-varying coefficients. The arterial network is modeled as a Finite Impulse Response (FIR) filter with unknown coefficients. A new tool for estimation of both the central arterial pressure and the unknown channel dynamics has been developed. The convolution process is modeled as a Finite Impulse Response (FIR) filter with unknown coefficients. The source signal is also unknown. Assuming that one of the FIR filter coefficients are time varying, we have been able to get accurate estimation results for the source signal, even through the filter order is unknown. The time varying filter coefficients have been estimated through the SC algorithm, and we have been able to deconvolve the measurements and obtain both the source signal and the convolution path. The positive results demonstrate that the SC approach is superior to conventional methods.
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