Problems in probabilistic induction are of two general kinds. In the first, we have a linearly ordered sequence of symbols that must be extrapolated. In the second we want to extr...
Diffusion processes which are widely used in low level vision are presented as a result of an underlying stochastic process. The short-time non-linear diffusion is interpreted as ...
The models used for analyzing functional MRI (fMRI) data have profound impact on the detection of active brain areas. In this paper temporal and spatial linear subspace models for...
We present an algebraic solution to direct registration of diffusion tensor images under various local deformation models. We show how to linearly recover the deformation from the...
— This paper studies the problem of stability analysis for neural networks (NNs) with a time-varying delay. The activation functions are assumed to be neither monotonic, nor diff...