Minimum norm algorithms for EEG source reconstruction are studied in view of their spatial
resolution, regularization, and lead-field normalization properties, and their computational …

We survey the field of magnetoencephalography (MEG) and electroencephalography (EEG)
source estimation. These modalities offer the potential for functional brain mapping with …

Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at
New Mexico Tech and is designed to be accessible to typical graduate students in the …

We propose a method to invert surface wave dispersion data directly for 3-D variations of
shear wave speed, that is, without the intermediate step of phase or group velocity maps …

A lucid explanation of the intricacies of both simple and complex least squares methods. As
one of the classical statistical regression techniques, and often the first to be taught to new …

Targeted audience• Specialists in numerical computations, especially in numerical optimiza
tion, who are interested in designing algorithms with automatie result ver ification, and who …

The Radon transform (RT) suffers from the typical problems of loss of resolution and aliasing
that arise as a consequence of incomplete information, including limited aperture and …

The timing of spring leaf development, trajectories of summer leaf area, and the timing of
autumn senescence have profound impacts to the water, carbon, and energy balance of …

We present a reconstruction algorithm that resolves cellular tractions in diffraction-limited
nascent adhesions (NAs). The enabling method is the introduction of sparsity regularization …

This book describes the theory and practice of inverting seismic data for the subsurface rock
properties of the earth. The primary application is for inverting reflection and/or transmission …