78 research outputs found

    Analytic Formulas for Alternating Projection Sequences for the Positive Semidefinite Cone and an Application to Convergence Analysis

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    We find analytic formulas for the alternating projection method for the cone S+n\mathbb{S}^n_+ of positive semidefinite matrices and an affine subspace. More precisely, we find recursive relations on parameters representing a sequence constructed by the alternating projection method. By applying the formulas, we analyze the alternating projection method in detail and show that the upper bound given by the singularity degree is actually tight when the alternating projection method is applied to S+3\mathbb{S}^3_+ and a 33-plane whose intersection is a singleton and has singularity degree 22.Comment: 26 page

    Exact Convergence Rates of Alternating Projections for Nontransversal Intersections

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    We consider the convergence rate of the alternating projection method for the nontransversal intersection of a semialgebraic set and a linear subspace. For such an intersection, the convergence rate is known as sublinear in the worst case. We study the exact convergence rate for a given semialgebraic set and an initial point, and investigate when the convergence rate is linear or sublinear. As a consequence, we show that the exact rates are expressed by multiplicities of the defining polynomials of the semialgebraic set, or related power series in the case that the linear subspace is a line, and we also decide the convergence rate for given data by using elimination theory. Our methods are also applied to give upper bounds for the case that the linear subspace has the dimension more than one. The upper bounds are shown to be tight by obtaining exact convergence rates for a specific semialgebraic set, which depend on the initial points.Comment: 22 pages, 1 figur

    Induced Norm Analysis of Linear Systems for Nonnegative Input Signals

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    This paper is concerned with the analysis of the Lp (p∈[1,∞),p=∞)L_p\ (p\in[1,\infty), p=\infty) induced norms of continuous-time linear systems where input signals are restricted to be nonnegative. This norm is referred to as the Lp+L_{p+} induced norm in this paper. It has been shown recently that the L2+L_{2+} induced norm is effective for the stability analysis of nonlinear feedback systems where the nonlinearity returns only nonnegative signals. However, the exact computation of the L2+L_{2+} induced norm is essentially difficult. To get around this difficulty, in the first part of this paper, we provide a copositive-programming-based method for the upper bound computation by capturing the nonnegativity of the input signals by copositive multipliers. Then, in the second part of the paper, we derive uniform lower bounds of the Lp+ (p∈[1,∞),p=∞)L_{p+}\ (p\in[1,\infty), p=\infty) induced norms with respect to the standard LpL_{p} induced norms that are valid for all linear systems including infinite-dimensional ones. For each linear system, we finally derive a computation method of the lower bounds of the L2+L_{2+} induced norm that are larger than (or equal to) the uniform one. The effectiveness of the upper/lower bound computation methods are fully illustrated by numerical examples.Comment: 12 pages, 3 figures. A preliminary version of this paper was presented at ECC 2022 (arXiv:2401.03242) and IFAC WC 202

    Exploiting Sparsity in SDP Relaxation for Sensor Network Localization

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