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Neural network methods have recently been recognized as new and unconventional alternatives for RF and microwave modeling and design. An increasing number of RF and microwave engineers as well as researchers have begun take a serious interest in this emerging technology. Although a number of research papers on this topic have appeared in literature recently, there is no book describing this technology from RF/microwave engineers perspective. All the existing books on neural networks, written mostly for signal processing, pattern recognition, process control and so on, do not address RF and microwave modeling and design problems. The present book has been prepared with RF/microwave designers, researchers and graduate students as its primary audience. The subject of neural networks is described from the viewpoint of , and in the language of, RF and microwave engineers. The issues, challenges, formulations and solutions important to the RF and microwave areas are described uniquely in this book.

Following an introduction to RF/microwave design and neural networks in Chapter 1, we describe the RF and microwave process and problems and relate them to neural networks in Chapter 2. Chapters 3 and 4 describe various kinds of neural network structures and methods for training neural networks and thus provide ANN background needed in the following chapters. ANN modeling of various types of RF and microwave components is discussed in Chapter 5. Examples such as Transmission line structures, coplanar waveguide circuit design, and microstrip patch antennas are included. These component models can be linked to commercially available microwave network simulators. Use of ANN models for optimizing the geometry of some of these components is also discussed. ANN modeling of interconnects used in high speed digital circuits, as well as in RF and microwave circuits is the topic of Chapter 6. Development of small-signal and large-signal models for various active devices like FETs, HBTs, and HMETs is the topic of Chapter 7. This is followed by a chapter that describes, specifically for RF and microwave designers, how to incorporate neural network models in circuit simulation and design. Examples of optimization of CPW circuits, patch antennas, multilayer filters and amplifiers are included. Chapter 9 highlights a unique and exciting technical area, combining prior RF and microwave knowledge with neural networks leading to a methodology for knowledge-based design for RF and microwave circuits. The book concludes with a chapter summarizing the concepts presented in previous chapters, and discussing some of the emerging trends for the future research and development in this exciting field.