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Shankarachary Ragi (shankarachary.ragiasu.edu) Abstract: In this study, we develop heuristic methods to solve unimodular quadratic programming (UQP) approximately, which is known to be NPhard. UQPtype problems appear naturally in radar waveform design and active sensing applications. In the UQP framework, we optimize a sequence of complex variables with unit modulus by maximizing a quadratic function. To solve the UQP problem approximately, we present two heuristic methods with polynomial complexity with respect to the size of the UQP problem. The first heuristic called dominanteigenvectormatching, where the solution is picked that matches the complex arguments of the dominant eigenvector of the Hermitian matrix in the UQP formulation. The second heuristic, a greedy strategy, is shown to provide a performance guarantee of (1 1=e) with respect to the optimal solution given that the UQP objective function possesses a property called string submodularity. We demonstrate the performance of these heuristics via numerical simulations. Keywords: Unimodular quadratic programming, radar waveform design, active sensing, approximation methods, string submodular Category 1: Applications  Science and Engineering Citation: Download: [PDF] Entry Submitted: 12/12/2016 Modify/Update this entry  
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