A convex optimization model for finding non-negative polynomials
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摘要
This paper presents a convex optimization model for the problem of finding some polynomials for which certain linear combinations are non-negative polynomials. This model is then applied to solve several filter design problems. We first reformulate some low-pass filter design problems, with finite or infinite impulse response, as optimization problems over non-negative (real or complex) polynomials whose feasibility problems can be solved by applying our model. The whole optimization problems are then solved by using a combination of a bisection search procedure on an appropriate parameter and our convex optimization model to solve the feasibility problems. Some numerical examples illustrate the method.
论文关键词:Non-negative polynomial,Sum of squares,Sum of square magnitudes of polynomials,Filter design problem
论文评审过程:Received 1 August 2015, Revised 27 December 2015, Available online 1 February 2016, Version of Record 17 February 2016.
论文官网地址:https://doi.org/10.1016/j.cam.2016.01.018