… are iterative in nature. Theprojection onto convex sets (POCS) methods and iterative optimization
… The purpose of this paper is to give a unified treatment of several of these algorithms. …

… to iterative algorithm. The key for developing correct iterative program is loop invariant.
This is recognized by not only the advocators of formal method of designing algorithms and …

… by fixed point iteration methods; in particular, iterative methods used in … iterative method
which is based on an infinite pool of operators in this subclass. The perturbation resilient iterative …

… We presented a unified treatment of BSS algorithms for convolutive mixtures. This framework
contains two main principles: Firstly, three fundamental signal properties, nonwhiteness, …

… The main goal of this paper is to propose a unified algorithm framework for two classes of
convex optimization problems arising from sparse reconstruction. The framework proposed …

… siderable design freedom in the iteration-dependent behavior of the algorithm. Finally, we
… of MM algorithms based on connected (eg, convex) tangent majorants. For such algorithms, …

… However, one advantage of the GFM-bound over the spectral radius is its generic aspect
allowing it to be applied to many iterative algorithms, even those having an iteration matrix with …

… of algorithms for finding solutions of this problem and establish the corresponding strong
convergence theorems for the sequences generated by our algorithms. … through our algorithms. …

… by κ and all subsequent iterations were performed with a stepsize of s = κ. To test the
convergence behaviour with different stepsizes s, we performed iterative algorithmic runs with s = …

… all the algorithms in Table 1 use the same unified model, and they thus all have the same
aim: optimize the values in the ‘unified model parameter vector’. These algorithms only differ in …