On the convergence properties of the projected gradient method for convex optimization

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Strong Convergence of Projected Subgradient Methods for Nonsmooth and Nonstrictly Convex Minimization (2008, background): “Most of the related convergence results deal with Armijo-type rules for choosing the stepsizes [5, 13, 15 , 25].”
Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems (2007, methodology): “Convergence of the methods proposed above can be derived from the analysis of Bertsekas [3] and Iusem [33], but follows most directly from the results of Birgin, Martinez, and Raydan [4] and Serafini, Zanghirati, and Zanni [51].”