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Surrogate-Based Circuit Design Centering

In: Surrogate-Based Modeling and Optimization

Author

Listed:
  • Abdel-Karim S. O. Hassan

    (Cairo University, Engineering Mathematics and Physics Department, Faculty of Engineering)

  • Ahmed S. A. Mohamed

    (Cairo University, Engineering Mathematics and Physics Department, Faculty of Engineering)

Abstract

Circuit design centering is one of the most important problems concerning the optimal design of circuits. Circuit design centering seeks nominal values of designable circuit parameters that maximize the probability of satisfying the design specifications (yield function). Design centering can be performed geometrically by finding the center of the feasible region (region in the designable parameter space where the design specifications are satisfied), or by maximizing the yield function explicitly. For all cases, the high expense of circuit simulations required obstructs the design centering process, especially for microwave circuits. To overcome this, computationally cheap surrogate-based models (e.g., space mapping, response surfaces, kriging, and neural networks) can be used for approximating the response functions or the yield function itself. In this chapter the design centering problem is formulated as an optimization problem, and the estimation of the yield function through several sampling techniques is explained. The difficulties facing the design centering process, especially for microwave circuits, are discussed, and the role of surrogate-based models in overcoming these difficulties is demonstrated. Special interest is devoted to space mapping surrogates and microwave circuit design centering. Some of the important surrogate-based circuit design centering approaches are reviewed with an overview of their theoretical bases. Tutorial and practical circuit examples are given to show the effectiveness of these approaches.

Suggested Citation

  • Abdel-Karim S. O. Hassan & Ahmed S. A. Mohamed, 2013. "Surrogate-Based Circuit Design Centering," Springer Books, in: Slawomir Koziel & Leifur Leifsson (ed.), Surrogate-Based Modeling and Optimization, edition 127, pages 27-49, Springer.
  • Handle: RePEc:spr:sprchp:978-1-4614-7551-4_2
    DOI: 10.1007/978-1-4614-7551-4_2
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