Asymptotic waveform evaluation for S-domain solution of electromagnetic devices

Bracken, J.E.; Cendes, Z.J.

doi:10.1109/20.717758

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…It is known that Simplex Method and BIM are clearly established in [7,8], So they are not referred in this paper. (1)…”

Section: B Simplex Methods and Bimmentioning

confidence: 96%

“…To handle such high dimensionality, HPSO [3][4][5][6] is exploited to reconstruct a dielectric target, in a two-dimensional geometry. For the HPSO, firstly, the initial swarm is initialized incorporated with the information obtained from Born approximation; Secondly, the best particle will be optimized by Simplex Algorithm; and at last, the positions will be optimized by Born Iteration Method [7,8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Microwave Imaging Based on the AWE and HPSO Incorporated with the Information Obtained from Born Approximation

Huang

Wang

Liu

2010

2010 International Conference on Computational Intelligence and Software Engineering

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A novel approach for microwave imaging of the dielectric objects in free space using hybrid particle swarm optimization (HPSO) is presented in this paper. A scattering model based on the method of moment and the asymptotic waveform evaluation (AWE) is used to solve the scattering problem in this paper. The error between measured field and computed field is considered as the object function. The inverse scattering problem is transferred into an optimization problem by minimizing the object function, which is solved by hybrid particle swarm optimization. Comparisons of the Genetic Algorithms (GA) and hybrid particle swarm optimization are carried out. The results show that hybrid particle swarm optimization has the excellent performance imaging precision and robust anti-jamming. Another important advantage is that there is no necessary to utilize the regularization term which is essential to obtain the stabilization in application of typical direct optimization routine.

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“…It is known that Simplex Method and BIM are clearly established in [7,8], So they are not referred in this paper. (1)…”

Section: B Simplex Methods and Bimmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Microwave Imaging Based on the AWE and HPSO Incorporated with the Information Obtained from Born Approximation

Huang

Wang

Liu

2010

2010 International Conference on Computational Intelligence and Software Engineering

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“…Then, in 1994 and 1995, techniques based on the Lanczos process [3] from 1950 appeared in [4] and [5]; in those works, systems that are linear in the MORe parameter are converted into Padé approximations without explicitly forming Manuscript the ill-conditioned moments. Improvements to the Padé approximation via the Lanczos process (PVL) resulted in the sweep [6], which is used to simulate electromagnetics problems modeled using the boundary element method in [7] and to compute the scattering parameters of microwave devices in [8]. In addition to the Lanczos process, another Krylov subspace technique from the 1950s called the Arnoldi process [9] also found applications in the 1990s in problems that were linear in the MORe parameter [10].…”

Section: Introductionmentioning

confidence: 98%

Well-conditioned asymptotic waveform evaluation for finite elements

Slone

Lee

2003

IEEE Trans. Antennas Propagat.

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The frequency-domain finite-element method (FEM) results in matrix equations that have polynomial dependence on the frequency of excitation. For a wide-band fast frequency sweep technique based on a moment-matching model order reduction (MORe) process, researchers generally take one of two approaches. The first is to linearize the polynomial dependence (which will either limit the bandwidth of accuracy or require the introduction of extra degrees of freedom) and then use a well-conditioned Krylov subspace technique. The second approach is to work directly with the polynomial matrix equation and use one of the available, but ill-conditioned, asymptotic waveform evaluation (AWE) methods. For large-scale FEM simulations, introducing extra degrees of freedom, and therefore increasing the length of the MORe vectors and the amount of memory required, is not desirable; therefore, the first approach is not alluring. On the other hand, an ill-conditioned AWE process is unattractive. This paper presents a novel MORe technique for polynomial matrix equations that circumvents these problematic issues. First, this novel process does not require any additional unknowns. Second, this process is well-conditioned. Along with the presentation of the novel algorithm, which will be called well-conditioned AWE (WCAWE), numerical examples modeled using the FEM are given to illustrate its accuracy.Index Terms-Asymptotic waveform evaluation, computeraided engineering, fast frequency sweep, finite-element methods, model order reduction.

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“…The ÿrst class contains techniques which linearize the system by introducing extra degrees of freedom, then simulating the expanded, linearized system by using one of the well-conditioned Krylov subspace generating techniques such as the Lanczos [1] or the Arnoldi [2] processes which were popularized by the works [3][4][5][6]. Examples of the ÿrst class are included in References [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Broadband model order reduction of polynomial matrix equations using single‐point well‐conditioned asymptotic waveform evaluation: derivations and theory

Slone

Lee

2003

Numerical Meth Engineering

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SUMMARYTo e ect a model order reduction (MORe) process on a system which has a polynomial matrix equation dependence on the MORe parameter, researchers generally take one of two approaches. The ÿrst is to linearize the system by introducing extra degrees of freedom and then to solve the resulting expanded, linear system with a method such as Lanczos or Arnoldi. The second approach is to work directly with the polynomial system and use a technique such as asymptotic waveform evaluation (AWE). Of course, each approach has advantages and disadvantages. In this paper, a new technique will be presented which has some desirable characteristics from both approaches and which is able to circumvent simultaneously some of their disadvantages. It can be shown that both the Arnoldi and the AWE methods are special cases of this new technique. Finally, numerical results will show the viability of the new method, which will be called the well-conditioned asymptotic waveform evaluation (WCAWE) method.

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Asymptotic waveform evaluation for S-domain solution of electromagnetic devices

Cited by 6 publications

References 5 publications

Microwave Imaging Based on the AWE and HPSO Incorporated with the Information Obtained from Born Approximation

Microwave Imaging Based on the AWE and HPSO Incorporated with the Information Obtained from Born Approximation

Well-conditioned asymptotic waveform evaluation for finite elements

Broadband model order reduction of polynomial matrix equations using single‐point well‐conditioned asymptotic waveform evaluation: derivations and theory

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