Proceedings ArticleDOI
Comparison of optimization techniques for coupling matrix synthesis using eigenvalue based approach
Andrzej Jedrzejewski,Lukasz Szydlowski,Adam Lamecki +2 more
- Vol. 2, pp 471-475
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TLDR
In this article, a comparison of the optimization techniques used for coupling matrix synthesis problem involving cost function constructed from eigenvalues of coupling matrix as well as eigen values of principal sub-matrices is presented.Abstract:
This paper presents a comparison of the optimization techniques used for coupling matrix synthesis problem involving cost function constructed from eigenvalues of coupling matrix as well as eigenvalues of principal sub-matrices. Minimization of cost function is performed via three different optimization techniques: linear least-square problem (LL-S), Nelder — Mead (N-M) and quasi — Newton (q-N). The efficiency of linear least-squares method for various starting points is tested. Convergence of the optimization routines are improved through analytically obtained derivatives and trust region (TR) which limits the search area at each iteration step. Examples of the synthesis of cross-coupled filters with symmetric and asymmetric responses are presented.read more
Citations
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Proceedings ArticleDOI
Coupling matrix filter synthesis based on reflection matrices
TL;DR: It is shown that reflection matrices are complementary to rotationMatrices a useful concept that can be used alternatively to rotation matrices in the similarity transformations that are applied in order to transform the coupling matrix to a suitable form.
Journal ArticleDOI
Computational Cost Reduction for N+2 Order Coupling Matrix Synthesis Based on Desnanot-Jacobi Identity
TL;DR: The results show that it is possible to decrease the computational complexity, reduce the associated cost function, and under certain circumstances obtain different equivalent solutions of the Desnanot–Jacobi identity.
References
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Numerical Optimization
Jorge Nocedal,Stephen J. Wright +1 more
TL;DR: Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization, responding to the growing interest in optimization in engineering, science, and business by focusing on the methods that are best suited to practical problems.
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Conditioning of Quasi-Newton Methods for Function Minimization
TL;DR: In this paper, a class of approximating matrices as a function of a scalar parameter is presented, where the problem of optimal conditioning of these matrices under an appropriate norm is investigated and a set of computational results verifies the superiority of the new methods arising from conditioning considerations to known methods.
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Numerical Methods Using MATLAB
John H. Mathews,Kurtis D. Fink +1 more
TL;DR: This book helps the reader understand the broad area of MATLAB application and enables the reader to grasp complex but widely applied concepts in the important field of optimization.
Journal ArticleDOI
General coupling matrix synthesis methods for Chebyshev filtering functions
TL;DR: In this article, a simple recursion technique is described for the generation of the polynomials for even or odd-degree Chebyshev filtering functions with symmetrically or asymmetrically prescribed transmission zeros and/or group delay equalization zero pairs.
Journal ArticleDOI
Synthesis of cross-coupled resonator filters using an analytical gradient-based optimization technique
TL;DR: In this paper, a general approach to the synthesis of cross-coupled resonator filters using an analytical gradient-based optimization technique is proposed, where the gradient of the cost function with respect to changes in the coupling elements between the resonators is determined analytically.
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