Conventional sparse phase retrieval schemes can recover signals from the magnitude of linear measurements only up to a global ambiguity. This work proposes novel approach that instead utilizes affine achieve ambiguity-free signal reconstruction. The proposed method relies on two-stage consists support identification followed by exact recovery nonzero entries. In noise-free case, perfect using s...

in this paper, an algorithm is presented for the formation of optimal null basis vectors corresponding to sparse flexibility matrices. for controlling the independence of the vectors, a generator is selected in each corresponding self-equilibrating systems, and the sequence of generators is modeled as decision variables. since the equilibrium conditions and uniqueness of generators consists a u...

A female one month old with features supporting a diagnosis of neonatal progeroid syndrome(WRS)  presented to our neonatology section of GB pant children hospital Srinagar .she had prenatal and post natal growth failure, generalized lipotrophy, triangular face, psedohydrocephalous, sparse scalp hair and eye brows, prominent scalp veins and greatly widened anterior fontenella.

We give some new results on sparse signal recovery in the presence of noise, for weighted spaces. Traditionally, were used dictionaries that have the norm equal to 1, but, for random dictionaries this condition is rarely satised. Moreover, we give better estimations then the ones given recently by Cai, Wang and Xu.