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AAK Theorem and a Design of Multidimensional BIBO Stable Filters
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作者 Bossoto Bossoto Gabriel Bissanga 《Open Journal of Discrete Mathematics》 2024年第2期9-15,共7页
Rational approximation theory occupies a significant place in signal processing and systems theory. This research paper proposes an optimal design of BIBO stable multidimensional Infinite Impulse Response filters with... Rational approximation theory occupies a significant place in signal processing and systems theory. This research paper proposes an optimal design of BIBO stable multidimensional Infinite Impulse Response filters with a realizable (rational) transfer function thanks to the Adamjan, Arov and Krein (AAK) theorem. It is well known that the one dimensional AAK results give the best approximation of a polynomial as a rational function in the Hankel semi norm. We suppose that the Hankel matrix associated to the transfer function has a finite rank. 展开更多
关键词 multidimensional filter DESIGN BIBO Stability Optimal AAK Theorem Transfer Function Hankel Matrix
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A MULTIDIMENSIONAL FILTER SQP ALGORITHM FOR NONLINEAR PROGRAMMING 被引量:1
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作者 Wenjuan Xue Weiai Liu 《Journal of Computational Mathematics》 SCIE CSCD 2020年第5期683-704,共22页
We propose a multidimensional filter SQP algorithm.The multidimensional filter technique proposed by Gould et al.[SIAM J.Optim.,2005]is extended to solve constrained optimization problems.In our proposed algorithm,the... We propose a multidimensional filter SQP algorithm.The multidimensional filter technique proposed by Gould et al.[SIAM J.Optim.,2005]is extended to solve constrained optimization problems.In our proposed algorithm,the constraints are partitioned into several parts,and the entry of our filter consists of these different parts.Not only the criteria for accepting a trial step would be relaxed,but the individual behavior of each part of constraints is considered.One feature is that the undesirable link between the objective function and the constraint violation in the filter acceptance criteria disappears.The other is that feasibility restoration phases are unnecessary because a consistent quadratic programming subproblem is used.We prove that our algorithm is globally convergent to KKT points under the constant positive generators(CPG)condition which is weaker than the well-known Mangasarian-Fromovitz constraint qualification(MFCQ)and the constant positive linear dependence(CPLD).Numerical results are presented to show the efficiency of the algorithm. 展开更多
关键词 Trust region multidimensional filter Constant positive generators Global convergence Nonlinear programming
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