Contemporary high-frequency engineering design heavily relies on full-wave electromagnetic (EM) analysis. This is primarily due to its versatility and ability to account for phenomena that are important from the point of view of system performance. Unfortunately, versatility comes at the price of a high computational cost of accurate evaluation. Consequently, utilization of simulation models in the design processes is challenging although highly desirable. The aforementioned problems can be alleviated by means of surrogate modeling techniques, the most popular of which are data-driven models. Although a large variety of methods are available, they are all affected by the curse of dimensionality. This is especially pronounced in high-frequency electronics, where typical system responses are highly nonlinear. Construction of practically useful surrogates covering wide ranges of parameters and operating conditions is a considerable challenge.Surrogate Modeling for High-Frequency Design presents a selection of works representing recent advancements in surrogate modeling and their applications to high-frequency design. Some chapters provide a review of specific topics such as neural network modeling of microwave components, while others describe recent attempts to improve existing modeling methodologies. Furthermore, the book features numerous applications of surrogate modeling methodologies to design optimization and uncertainty quantification of antenna, microwave, and analog RF circuits.Key Features: oProvides various surrogate modelling methodologies, practical guidelines and recommendations concerning application of the specific methods for solving practical design problems, as well as a number of setups that can be used to speed up the optimization processes even if only bits and pieces are utilized over the complete algorithmsoContains introductory material on both data-driven and physics-based surrogate modelling, paving the path for the reader to obtain fundamental knowledge of the fieldoReviews specific aspects of surrogate modelling, including popular techniques widely applied in high-frequency electronics (e.g., neural networks, kriging interpolation, co-kriging)oExpounds upon novel approaches in selected areas (e.g., uncertainty quantification using polynomial chaos expansion models, constrained modelling)oOffers an overview of developments and applications of inverse modelling methods to expedited design of high-frequency structuresoLists application case studies concerning design, statistical analysis, and yield optimization of antennas, microwave structures, active circuits, as well as analog/RF devices

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