Hidden Convexity in QCQP with Toeplitz-Hermitian Quadratics PROJECT TITLE :Hidden Convexity in QCQP with Toeplitz-Hermitian QuadraticsABSTRACT:Quadratically Constrained Quadratic Programming (QCQP) includes a broad spectrum of applications in engineering. The overall QCQP problem is NP-Exhausting. This text considers QCQP with Toeplitz-Hermitian quadratics, and shows that it possesses hidden convexity: it can always be solved in polynomial-time via Semidefinite Relaxation followed by spectral factorization. Furthermore, if the matrices are circulant, then the QCQP can be equivalently reformulated as a linear program, that will be solved very efficiently. An application to parametric power spectrum sensing from binary measurements is included to illustrate the results. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Drawing Conclusions from Linked Data on the Web: The EYE Reasoner Social Networking Reduces Peak Power Consumption in Smart Grid