This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
This paper gives a widely applicable technique for solving many of the parameter estimation problems encountered in geometric computer vision. A commonly used approach is to minim...
Abstract. We present a refined method for rotation estimation of signals on the 2-Sphere. Our approach utilizes a fast correlation in the harmonic domain to estimate rotation angle...
Abstract. In this article we study the problem of estimating the parameters of a 2-D electrophysiological model of the heart from a set of temporal recordings of extracellular pote...