The performance of DF-based beamformers is seriously degraded in situations where the array is imprecisely calibrated, or when the spatial coherence of the signal wavefronts is perturbed. When the calibration errors or perturbation may be characterized by a set of parameters drawn from a known Gaussian distribution , a maximum a posteriori (MAP) estimator may be used to separately estimate the ...

When performing any real-time detection task, such as face detection, speech recognition, etc., we can take advantage of the temporal correlations within the data stream. This can help us make detection more robust by using anticipations about the target to overcome the variance due to noise. We present an extended self-organized map that uses lateral weights between the nodes to learn temporal...

In this paper, we present an information theoretic analysis of the blind signal classification algorithm. We show that the algorithm is equivalent to a Maximum A Posteriori (MAP) estimator based on estimated parametric probability models. We prove a lower bound on the error exponents of the parametric model estimation. It is shown that the estimated model parameters converge in probability to t...

In most situations the best estimator of a function of the parameter exists, but sometimes it has a complex form and we cannot compute its variance explicitly. Therefore, a lower bound for the variance of an estimator is one of the fundamentals in the estimation theory, because it gives us an idea about the accuracy of an estimator. It is well-known in statistical inference that the Cram&eac...

Titterington proposed a recursive parameter estimation algorithm for finite mixture models. However, due to the well known problem of singularities and multiple maximum, minimum and saddle points that are possible on the likelihood surfaces, convergence analysis has seldom been made in the past years. In this paper, under mild conditions, we show the global convergence of Titterington’s recursi...

Reduced basis approximations for geometrically parametrized advection-diffusion equations are investigated. The parametric domains are assumed to be images of a reference domain through a piecewise polynomial map; this may lead to nonaffinely parametrized diffusion tensors that are treated with an empirical interpolation method. An a posteriori error bound including a correction term due to thi...

OBJECTIVE The value of different algorithms that estimate cardiac output (CO) by analysis of a peripheral arterial blood pressure (ABP) waveform has not been definitively identified. In this investigation, we developed a testing data set containing a large number of radial ABP waveform segments and contemporaneous reference CO by thermodilution measurements, collected in an intensive care unit ...