This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
Future progress in neuroscience hinges on reconstruction of neuronal circuits to the level of individual synapses. Because of the specifics of neuronal architecture, imaging must ...
Ashok Veeraraghavan, Alex Genkin, Shiv Vitaladevun...
Takens' Embedding Theorem remarkably established that concatenating M previous outputs of a dynamical system into a vector (called a delay coordinate map) can be a one-to-one...
The problem of recovering the sparsity pattern of a fixed but unknown vector β∗ ∈ Rp based on a set of n noisy observations arises in a variety of settings, including subset...
Finding an accurate sparse approximation of a spectral vector described by a linear model, when there is available a library of possible constituent signals (called endmembers or ...