BACKGROUND The accuracy of EEG source localization depends on a sufficient sampling of the surface potential field, an accurate conducting volume estimation (head model), and a suitable and well-understood inverse technique. The goal of the present study is to examine the effect of sampling density and coverage on the ability to accurately localize sources, using common linear inverse weight te...

Our acoustic to articulatory inversion method exploits an original codebook representing the articulatory space by hypercubes. The articulatory space is decomposed into regions where the articulatory-to-acoustic mapping is linear. Each region is represented by a hypercube. The inversion procedure retrieves articulatory vectors corresponding to an acoustic entry from the hypercube codebook. The ...

This paper discusses simulation from an absolutely continuous distribution on the positive real line when the Laplace transform of the distribution is known but its density and distribution functions may not be available. We advocate simulation by the inversion method using a modified Newton-Raphson method, with values of the distribution and density functions obtained by numerical transform in...

Online Goal Babbling and Direction Sampling are recently proposed methods for direct learning of inverse kinematics mappings from scratch even in high-dimensional sensorimotor spaces following the paradigm of ”learning while behaving”. To learn inverse statics mappings – primarily for gravity compensation – from scratch and without using any closed-loop controller, we modify and enhance the Onl...

This paper explains and demonstrates a model-following controller design based on the stabilized digital inverse system. Conventional digital inverse systems are constructed behind a plant to estimate unknown disturbances. Herein, the inverse system is designed in front of the plant. The model-following controller is then constructed on the basis of this structure. However, when the relative de...

We consider the problem of spatiotemporal sampling in which an initial state f of an evolution process ft = Atf is to be recovered from a combined set of coarse samples from varying time levels {t1, . . . , tN}. This new way of sampling, which we call dynamical sampling, differs from standard sampling since at any fixed time ti there are not enough samples to recover the function f or the state...

We propose two algorithms for sampling from two gamma variates possessing a negative correlation. The case of positive correlation is easily solved, so we just mention it. The main problem is the lowest value of the correlation coefficient that can be reached. The starting point of both algorithms is generation from a bivariate density with uniform negatively correlated marginals. Actually the ...

We introduce a sampling-based motion planning method that automatically adapts to the difficulties caused by thin regions in the free space (not necessarily narrow corridors). These problems arise frequently in settings such as closedchain manipulators, humanoid motion planning, and generally any time bodies are in contact or maintain close proximity with each other. Our method combines the agg...

S U M M A R Y In most geophysical inverse problems the properties of interest are parametrized using a fixed number of unknowns. In some cases arguments can be used to bound the maximum number of parameters that need to be considered. In others the number of unknowns is set at some arbitrary value and regularization is used to encourage simple, non-extravagant models. In recent times variable o...