### Faarfannaa haaraa 2020

Estimates the 1-norm of a square matrix, using reverse communication for evaluating matrix-vector products. These routinese are thread safe version of Rlacon/Clacon. Rgecon-- dgecon - Rgecon estimates the reciprocal of the condition number of a general real matrix A, in either the 1-norm or the infinity-norm A vector norm is a real valued function that satisfies the following properties: Basic examples of vector norms •Check that these are norms using the definition! When no index is specified on a norm (e.g., this is considered to be the Euclidean norm. • For the three norms above, we have the relation • 1 norm of a vector over an aﬃne space returns the sparsest vector in that space (see, e.g., [6, 5, 3]). There is a strong parallelism between the sparse approximation and rank minimization settings. The rank of a diagonal matrix is equal to the number of non-zeros on the diagonal. Similarly, the sum of the singular values of a the signalÕs sparse coefficient vector in the (N " M)-dimensional translated null space H = N (# ) + s.! Minimum '2 norm reconstruction : Define the ' p norm of the vector s as ($s$p)p = # N i= 1 | si| p. The classical approach to inverse problems of this type is to find the vector in the trans-lated null space with the smallest '2 norm (energy) by solving