Optimization Theory and Algorithms
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In this book, we have considered features which are defined by some optimality properties, such as maximum sparseness. In this chapter, we briefly explain how those optimal features can be numerically computed. The solutions are based either on general-purpose optimization methods, such as gradient methods, or specific tailor-made methods such as fixed-point algorithms.