Search

Norm retrieval was introduced for Hilbert space frames for the first time by Bahmanpour et. al. in the year 2015. In order for a subspace as well as its orthogonal complement to do norm retrieval, it was proved by Bahmanpour et. al. that norm retrieval is a necessary requirement. Basically, norm retrieval refers to the process of reconstructing the signal's norm from the intensity measurements. We give a few characterizations for norm retrieval by vectors and subspaces under the action of bounded linear operators. [ABSTRACT FROM AUTHOR]

Norm retrieval was introduced for Hilbert space frames for the first time by Bahmanpour et. al. in the year 2015. In order for a subspace as well as its orthogonal complement to do norm retrieval, it was proved by Bahmanpour et. al. that norm retrieval is a necessary requirement. Basically, norm retrieval refers to the process of reconstructing the signal's norm from the intensity measurements. We give a few characterizations for norm retrieval by vectors and subspaces under the action of bounded linear operators. [ABSTRACT FROM AUTHOR]

Fusion frames are widely studied for their applications in recovering signals from large data. These are proved to be very useful in many areas, for example, wireless sensor networks. In this paper, we discuss a generalization of fusion frames, K-fusion frames. K-fusion frames provide decompositions of a Hilbert space into atomic subspaces with respect to a bounded linear operator. This article studies various kinds of properties of K-fusion frames. Several perturbation results on K-fusion frames are formulated and analyzed. [ABSTRACT FROM AUTHOR]