Abstract not found

Abstract—Many problems in signal processing and statistical inference involve finding sparse solutions to under-determined, or ill-conditioned, linear systems of equations. A standard approach consists in minimizing an objective function which includes a quadratic (squared ℓ2) error term combined

A unified approach to solve ill-posed inverse problems in econometrics

doi:10.1088/0266-5611/24/4/045010 Solution of the nonlinear elasticity imaging inverse problem: the compressible case

doi:10.1088/0266-5611/25/3/035004 On multiple level-set regularization methods for inverse problems

doi:10.1088/0266-5611/24/3/034011 Adaptive finite element methods for the solution of inverse problems in optical tomography

inverse problems

A simple solution is given to the problem of finding the unknown boundary from the extra boundary condition.

� When we design solutions, there are similar patterns that emerge to seemingly unrelated problems Design is part recognizing the ‘problem within the problem’ � If we want to communicate at a higher level we need a vocabulary around that � A design pattern is just that – a pattern that has been

In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available measurements is smaller than the dimension of the model to be estimated. However in many practical situations of interest, models