## Abstract We review the latest developments in spaceβmappingβbased modeling techniques with applications in microwave engineering. We discuss the two techniques that utilize a combination of standard space mapping and function approximation methodologies, in particular fuzzy systems and support v
Simplified space-mapping approach to enhancement of microwave device models
β Scribed by Qingsha S. Cheng; Slawomir Koziel; John W. Bandler
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 618 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1096-4290
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β¦ Synopsis
In this article, we present advances in microwave and RF device modeling exploiting the space mapping (SM) technology. New SM-based modeling techniques are proposed that are easy to implement entirely in the Agilent ADS framework. A simplified SM-based model description is discussed. Using a two-section transformer example, we show how the modeling accuracy is affected by the model flexibility. Tables, diagrams, and flowcharts are developed to help in understanding the concepts. This makes the SM modeling concept available to engineers through widely used commercial software. Our approach permits the creation of library models that can be used for model enhancement of microwave elements. Frequency-interpolation techniques are discussed and implemented. A set of four different SM-based models is presented along with corresponding implementations in the ADS schematic for a microstrip right-angle bend and a microstrip shaped T-junction. We use a three-section transformer to illustrate the implementation procedure in full details. We apply the technique to a more complicated HTS filter modeling problem. Fine-model data is obtained from Sonnet's em. We discuss the relation between the model complexity and accuracy as well as further improvement of the model.
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## Abstract We review recent developments in space mapping techniques for modeling of microwave devices. We present a surrogate modeling methodology that utilizes space mapping combined with radial basis function interpolation. The method has advantages both over the standard space mapping modeling
We present an accurate modeling technique that exploits standard space mapping (SM) as a trend function and the correction layer implemented with kriging. The kriging process allows us to efficiently utilize all available fine model data (not possible in the standard SM approach) and to obtain accur