Summary. In this paper we demonstrate model order reduction of a nonlinear academic model of a diode chain. Two reduction methods, which are suitable for nonlinear differential algebraic equation systems are used, the trajectory piecewise linear approach and the proper orthogonal decomposition with missing point estimation.

Summary.In this paper we demonstrate model order reduction for a nonlinear academic model of a diode chain. Two reduction methods, which are suitable for nonlinear differential algebraic equation systems are used, the Trajectory PieceWise Linear approach and the Proper Orthogonal Decomposition with Missing Point Estimation.

Summary. Sensitivity analysis is an important tool that can be used to assess and improve the design and accuracy of a model describing an electronic circuit. Given a model description in the form of a set of differential-algebraic equations it is possible to observe how a circuit's output reacts to varying input parameters, which are introduced at the requirements stage of design. In this paper we consider the adjoint method more closely. This method is efficient when the number of parameters is large. We extend the transient sensitivity work of Petzold et al., in particular we take into account the parameter dependency of the dynamic term. We also compare the complexity of the direct and adjoint sensitivity and derive some error estimates. Finally we sketch out how Model Order Reduction techniques could be used to improve the efficiency of adjoint sensitivity analysis.

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Summary. The" General Compound" multirate methods are attractive integration methods for the transient analysis of mixed analog-digital circuits. From a stability analysis, it follows that they have good stability properties.