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Author

Jian Song

Date of Award

4-1991

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Electrical Engineering

Supervisor

J. W. Bandler

Abstract

This thesis addresses itself to computer-aided yield-driver design of microwave circuits using implementable, efficient approximation and optimization techniques. Basic concepts of yield-driven design are identified. A number of approaches to statistical design are reviewed. Their features and limitations are discussed. The recent generalized ℓp centering approach and one-sided ℓ₁ optimization algorithm are addressed. A highly efficient quadratic approximation, specially applicable to statistical design, is presented. A set of very simple and easy-to-implement formulas is derived. This approximation technique is also applied to gradient functions of circuit responses to provide higher accuracy. A combined approach to attack large scale problem is presented, which explores the most powerful capabilities of hardware and software available to us, namely, the supercomputer, efficient quadratic modeling, fast and dedicated simulation, and state-of-the-art optimization. Yield-driven design techniques are extended to deal with tunable circuits by considering tuning tolerances. A 5-channel waveguide multiplexer is considered as an example both for the combined approach and for the treatment of tunable circuits. Yield-driven design of nonlinear microwave circuits with statistically characterized devices is considered. Relevant concepts are introduced. The efficient Integrated Gradient Approximation Technique (IGAT) is presented in the statistical design environment, which avoids the prohibitive computational burden resulting from the traditional perturbation scheme. A novel approach, called Feasible Adjoint Sensitivity Technique (FAST), is derived to calculate sensitivities of nonlinear circuits that are simulated in the harmonic balance environment. By taking advantage of the computational efficiency of adjoint analysis and the implementational simplicity of the perturbation technique, FAST is responsible for great savings of computational effort required for yield-driven design of nonlinear circuits.