Semidefinite Programming in Action

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This chapter examines an Lp-minimization program with interpolatory constraints as a way to introduce techniques commonly used in semidefinite programming. The case p = 2 reveals a link between positive semidefiniteness and Schur complements. The case p = ? illustrates the sum-of-squares techniques in connection with Riesz-Fejér theorem. The case p = 1 illustrates the method of moments in connection with the discrete trigonometric moment problem.