In this paper we describe a CAD environment for performance and yield driven circuit design with electromagnetic (EM) field simulations employed within the optimization loop. Microstrip structures are accurately simulated and their responses are incorporated into the overall circuit analysis. We unify the component level interpolation technique, devised to handle discretization of geometrical parameters, and the modeling technique used to lighten the computational burden of statistical design centering. We discuss the organization and utilization of the data base system integrated with the modeling technique. We demonstrate the feasibility and benefits of performance and yield optimization with EM simulations.>

We present exciting applications of the Huber concept in circuit modeling and optimization. By combining the desirable properties of the l/sub 1/ and l/sub 2/ norms, the Huber function is robust against gross errors and smooth w.r.t. small variations in the data. We extend the Huber concept by introducing a one-sided Huber function tailored to design optimization with upper and lower specifications. We demonstrate the advantages of Huber optimization in the presence of faults, large and small measurement errors, bad starting points and statistical uncertainties. Circuit applications include parameter identification, design optimization, statistical modeling, analog fault location and yield optimization.>

A simple, yet comprehensive proof of an important sensitivity formula for lossless two-ports stated by Orchard, Temes, and Cataltepe is presented. Our derivation invokes the principle of conservation of energy and the lossless property of the network under consideration and employs the Cauchy-Riemann equations of complex differentiation. Hence, it bears clear physical interpretation and mathematical elegance.

A novel method is presented to calculate exact first-order sensitivity formulas for nonreciprocal two-port power elements using the short-circuit admittance description. The method exploits an augmented Tellegen's theorem and is applied to an elegant adjoint transformer model to evaluate sensitivities with respect to control parameters of phase-shifting transformers.

In this paper, various fault location techniques in analog networks are described and compared. The emphasis is on the more recent developments in the subject. Four main approaches for fault location are addressed, examined, and illustrated using simple network examples. In particular, we consider the fault dictionary approach, the parameter identification approach, the fault verification approach, and the approximation approach. Theory and algorithms that are associated with these approaches are reviewed and problems of their practical application are identified. Associated with the fault dictionary approach we consider fault dictionary construction techniques, methods of optimum measurement selection, different fault isolation criteria, and efficient fault simulation techniques. Parameter identification techniques that either utilize linear or nonlinear systems of equations to identify all network elements are examined very thoroughly. Under fault verification techniques we discuss node-fault diagnosis, branch-fault diagnosis, subnetwork testability conditions as well as combinatorial techniques, the failure bound technique, and the network decomposition technique. For the approximation approach we consider probabilistic methods and optimization-based methods. The artificial intelligence technique and the different measures of testability are also considered. The main features of the techniques considered are summarized in a comparative table. An extensive, but not exhaustive, bibliography is provided.