Norm

Differences Between Two $ {L}_{1} $ Norm Minimization Schemes

Differences Between Two $ {L}_{1} $ Norm Minimization Schemes
  1. What is L1 norm minimization?
  2. What is L2 minimization?

What is L1 norm minimization?

L1-minimization refers to finding the minimum L1-norm solution to an underdetermined linear system b=Ax. Under certain conditions as described in compressive sensing theory, the minimum L1-norm solution is also the sparsest solution. In this paper, our study addresses the speed and scalability of its algorithms.

What is L2 minimization?

Adjustments of the observations are usually performed using the method of least squares, i.e. L2 norm minimisation that is based on the minimisation of the sum of the squares of the residuals, which permits the estimation of the most probable values of unknown parameters.

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