Model Reduction for Circuit Simulation

InhaltsangabePart I Invited Papers.1 The need for novel model order reduction techniques in the electronics industry;.W.H.A. Schilders. 1.1 Introduction. 1.2 Mathematical problems in the electronics industry. 1.3 Passivity and realizability. 1.4 Structure preservation. 1.5 Reduction of MIMO networks. 1.6 MOR for delay equations. 1.7 Parameterized and nonlinear MOR. 1.8 Summary: present and future needs of the electronics industry. References. 2 The SPRIM Algorithm for Structure-Preserving Order Reduction of General RCL Circuits; Roland W. Freund. 2.1 Introduction. 2.2 RCL Circuit Equations. 2.3 Projection-Based Order Reduction. 2.4 The SPRIM Algorithm. 2.5 Treatment of Voltage Sources. 2.6 Numerical Examples. 2.7 Concluding Remarks. References. 3 Balancing-Related Model Reduction of Circuit Equations Using Topological Structure; Tatjana Stykel. 3.1 Introduction. 3.2 Circuit equations. 3.3 Balancing-related model reduction. 3.4 Numerical methods for matrix equations. 3.5 Numerical examples. 3.6 Conclusions and open problems. References. 4 Topics in Model Order Reduction with Applications to Circuit Simulation; Sanda Lefteriu and Athanasios C. Antoulas. 4.1 Introduction and Motivation. 4.2 Background. 4.3 Theoretical Aspects. 4.4 Tangential interpolation for modeling Y-parameters. 4.5 Numerical Results. 4.6 Conclusion. References. Part II Contributed Papers.5 Forward and Reverse Modeling of Low Noise Amplifiers based on Circuit Simulations; L. De Tommasi, J. Rommes, T. Beelen, M. Sevat, J. A. Croon and T. Dhaene. 5.1 Introduction. 5.2 Forward and reverse modeling: problem descriptions. 5.3 Forward Modeling. 5.3.1 Performance Figures via Surrogate Models. 5.4 Reverse Modeling with the NBI method. 5.5 Reverse modeling using transistor level simulations. 5.6 Discussion and conclusions. References. 6 Recycling Krylov Subspaces for Solving Linear Systems with Successively Changing Right-Hand Sides Arising in Model Reduction; Peter Benner and Lihong Feng. 6.1 Introduction. 6.2 Methods Based on Recycling Krylov Subspaces. 6.3 Application to Model Order Reduction. 6.4 Simulation Results. 6.5 Conclusions. References. 7 Data-driven Parameterized Model Order Reduction Using z-domain Multivariate Orthonormal Vector Fitting Technique; Francesco Ferranti, Dirk Deschrijver, Luc Knockaert and Tom Dhaene. 7.1 Introduction. 7.2 Background. 7.3 Parametric Macromodeling. 7.4 Choice of basis functions. 7.5 Example: Double folded stub microstrip bandstop filter. 7.6 Conclusions. References. 8 Network Reduction by Inductance Elimination; M.M. Gourary, S.G.Rusakov, S.L.Ulyanov, and M.M.Zharov. 8.1 Introduction. 8.2 Elimination of RC-node by TICER. 8.3 Inductance Elimination. 8.4 Elimination of Coupled Inductances. 8.5 Eliminations under LC Couplings. 8.6 Algorithmic Aspects. 8.7 Numerical Examples. 8.8 Conclusion. References. 9 Simulation of coupled oscillators using nonlinear phase macromodels and model order reduction; Davit Harutyunyan and Joost Rommes. 9.1 Introduction. 9.2 Phase noise analysis of oscillators. 9.3 Oscillator coupled to a balun. 9.4 Oscillator coupling to a transmission line. 9.5 Model order reduction. 9.6 Numerical experiments. 9.7 Conclusion. References. 10 POD Model Order Reduction of Drift-Diffusion Equations in Electrical Networks; Michael Hinze, Martin Kunkel and Morten Vierling. 10.1 Introduction. 10.2 Complete coupled system. 10.3 Simulation of the full system. 10.4 Model reduction. 10.5 Numerical investigation. Appendix: Proper Orthogonal Decomposition. References. 11 Model Reduction of Periodic Descriptor Systems Using Balanced Truncation; Peter Benner, Mohammad-Sahadet Hossain and Tatjana Stykel. 11.1 Introduction. 11.2 Periodic Descriptor Systems. 11.3 Per